diff --git a/docs/DESIGN-E.md b/docs/DESIGN-E.md deleted file mode 100644 index 94a0e49..0000000 --- a/docs/DESIGN-E.md +++ /dev/null @@ -1,86 +0,0 @@ -# Design System — Landing Version E ("The Record") - -> This is a **separate** design system from `DESIGN.md`. `DESIGN.md` documents the -> cream + Space Grotesk system shared by versions A–D. Version E (`/e`) was built -> with the impeccable skill to test an independent design point of view against -> that hand-built system. **Copy and section order are identical to Version A** -> (the constant); only the visual system differs. `DESIGN.md` was intentionally -> left untouched. - -## Premise of the test -Judge an independent design's taste against the hand-built A–D system, holding copy -constant. Version A's exact words and section order are reused verbatim; every visual -decision (type, color, spacing, layout, motion) is made fresh. - -## Memorable thing -"AI that only acts on truth." Version E renders *verified* as a physical mark — a brass -highlight — so the page reads like a record where confirmed facts are sealed, not a -marketing page that asserts them. - -## Aesthetic direction -- **Lane:** brass-and-midnight forensic dossier / notary. Authority through precision. -- **Deliberately avoids** the three saturated 2026 reflexes for this category: SaaS-cream - minimalism, terminal-dark-green "operator" mode, and editorial-serif-italic. (A–D live - in the first two.) -- **Mood:** exacting, official, calm. A legal brief crossed with a measurement instrument. - -## Typography (3 families, loaded on the `/e` route only) -- **Display — Bricolage Grotesque.** Hero + section headings. Confident humanist grotesque; - not on any reflex-reject list and clearly distinct from A's Space Grotesk. -- **Body — Source Serif 4.** Document/record voice. Inverts the editorial reflex on purpose - (grotesque display + serif body, not the usual serif-display + sans-labels). -- **Mono — Spline Sans Mono.** Evidentiary metadata only: timestamps, exhibit labels, step - numbers, stat figures, kicker labels. Literal to the product (audit trail), not costume. -- Loaded via `next/font/google` in `app/app/e/page.tsx`, exposed as `--ve-display` / - `--ve-body` / `--ve-mono`. Scale uses `clamp()` with a >=1.25 ratio; hero ceiling ~4.9rem. - -## Color (strategy: Committed) -Midnight ink drenches the anchor sections (hero, process, testimony, security, close, -footer); cool off-white paper carries the content sections; one brass signal means -"verified" — reaching past the obvious green=verified cultural pull. - -| Token | Value | Role | -|---|---|---| -| `--ink` | `#14161D` | Midnight blue-black ground (drenched sections) | -| `--ink-2` / `--ink-3` | `#1B1E27` / `#242833` | Raised surfaces on dark | -| `--paper` | `#F4F5F7` | Cool off-white body (NOT cream — chroma toward blue, not warm) | -| `--paper-2` | `#EBECF0` | Secondary light surface | -| `--prose` / `--prose-dim` | `#2B303B` / `#565C68` | Body / secondary text on paper | -| `--ink-prose` / `--ink-prose-dim` | `#E7E9EE` / `#A7ACB8` | Body / secondary text on ink | -| `--brass` / `--brass-bright` / `--brass-ink` | `#C79A3A` / `#E2B557` / `#8A6516` | The single "verified" signal | -| `--line` / `--line-dark` | `#DCDEE4` / `rgba(255,255,255,.10)` | Hairlines | - -All body/secondary text verified >= 4.5:1 against its background. - -## Layout & anti-slop reworks -Same sections as A, restructured to avoid AI tells: -- **Stat cards → evidence ledger.** The four metrics are a hairline-divided ledger, not four - identical bordered stat cards. -- **Icon-tile feature cards → alternating editorial exhibits.** Screenshots framed as - "exhibits" with mono captions; no rounded icon tiles above headings. -- **Quote cards → testimony.** Large serif pull-quotes separated by hairlines with mono - attributions, not a 3-card grid. -- **Security cards → datasheet.** A `
` spec list, not four icon cards. -- **No per-section eyebrows.** A's decorative one-word kickers ("Features", "Impact", - "Security") are dropped (chrome, not copy). Numbers appear **only** on the genuine - 4-step process, where the order carries meaning. -- **No side-stripe borders, no gradient text, no glassmorphism, no hero-metric template.** - -## Motion -- framer-motion. Ambitious staggered hero first-load (ease-out-expo); per-section reveals - scoped to what they reveal (not one uniform fade on everything); brass "verified" mark - wipes in under the keyword. -- `prefers-reduced-motion` honored globally: a media-query override plus framer-motion - `useReducedMotion()` so reveals render content immediately with no transform. - -## Tracking -`/e` renders `` (gtag + Clarity) and `e` was added to the -`VARIANTS` array in `app/middleware.ts`, so the `kc-landing-variant` cookie can be set to -`e` and PostHog registers it alongside A–D. **Merging activates a 5-way (20% each) split** -on production `/`. - -## Files -- `app/app/e/page.tsx` — server wrapper, loads the three fonts on this route only. -- `app/components/version-e.tsx` — the page (all sections + scoped CSS + motion), self-contained. -- `app/middleware.ts` — `VARIANTS` now includes `'e'`. -- `PRODUCT.md` — strategic context written by `/impeccable init`. diff --git a/docs/DESIGN.md b/docs/DESIGN.md deleted file mode 100644 index 5383b58..0000000 --- a/docs/DESIGN.md +++ /dev/null @@ -1,133 +0,0 @@ -# Design System — Knowcap Landing Page - -## Product Context -- **What this is:** Landing page for Knowcap — the trust layer for AI agents -- **Who it's for:** Odoo partners (beachhead), agencies, multi-company founders, regulated verticals -- **Space/industry:** Meeting intelligence → verified knowledge → agent actions -- **Project type:** Marketing landing page for a SaaS web app (knowcap.ai → app.knowcap.ai) - -## Memorable Thing -"AI that only acts on truth" — visitors leave thinking this is the one where humans confirm before agents act. - -## Aesthetic Direction -- **Direction:** Industrial/Utilitarian — function-first, clean, confident. Infrastructure for truth. -- **Decoration level:** Minimal — typography and whitespace carry everything. Dot pattern on dark hero as the only texture. -- **Mood:** Serious, professional, trustworthy. Not playful, not startup-y. Like Stripe's docs crossed with a legal brief. -- **Reference sites:** linear.app (craft), vercel.com (confidence), tana.inc (anti-positioning) - -## Typography -- **Display/Hero:** Space Grotesk — locked by VISION.md. -0.02em letter-spacing on large headings. -- **Body:** System sans (-apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif) — consistent with app. -- **Mono/Claims/Stats:** JetBrains Mono — used for key claims, statistics, timestamps, code snippets, and category labels. Makes the page feel like infrastructure, not marketing. -- **Loading:** Google Fonts `family=Space+Grotesk:wght@400;500;600;700&family=JetBrains+Mono:wght@400;500;600` -- **Scale:** - - Hero h1: clamp(2.2rem, 4.5vw, 3.2rem) bold - - Section h2: clamp(1.6rem, 3vw, 2.2rem) bold - - Eyebrow: 10.5px uppercase tracking-wider bold (Space Grotesk) - - Body: 15px / 1.6 line-height - - Card title: 15px semibold (Space Grotesk) - - Card body: 13px / 1.6 - - Small/meta: 12px - - Mono stats: 24-28px semibold (JetBrains Mono) - -## Color -- **Approach:** Restrained — one accent, color is rare and meaningful -- **Background:** #FBFAF8 (cream) — locked by VISION.md -- **Surface:** #FFFFFF (cards) -- **Background muted:** #F5F4F1 (secondary surfaces) -- **Border:** #E7E4DD — locked by VISION.md -- **Border hover:** #D9D5CC -- **Ink (primary text):** #18181B — locked by VISION.md -- **Ink secondary:** #4A4F5A -- **Ink muted:** #8A8F99 -- **Accent:** #1F6B3A (Knowcap green = verified = truth) — the ONLY accent color -- **Accent light:** #E8F5ED (green tint for badges/backgrounds) -- **Hero gradient:** linear-gradient(135deg, #18181B, #0A0A0A) -- **Dark sections:** Same hero gradient (used for hero, governance, CTA, footer) -- **Category colors (for 5-category visuals only):** - - Fact: #1F6B3A (green) - - Risk: #9B1D1D (red) - - Decision: #4A2FA8 (purple) - - Task: #1B4F8F (blue) - - Person: #8A5A12 (amber) -- **Semantic:** Success #1F6B3A, Warning #D97706, Error #9B1D1D - -## Spacing -- **Base unit:** 8px -- **Density:** Comfortable — not cramped, not airy -- **Scale:** 2xs(2) xs(4) sm(8) md(16) lg(24) xl(32) 2xl(48) 3xl(64) 4xl(88-96) -- **Section padding:** 88-96px vertical, 40px horizontal -- **Max content width:** 1100px centered -- **Card padding:** 24-28px -- **Card border-radius:** 12px (rounded-xl) -- **Button border-radius:** 8px (rounded-lg) -- **Pill border-radius:** 999px (rounded-full) - -## Layout -- **Approach:** Hybrid — dark hero for opening, cream body with mixed centered/left-aligned content -- **Grid:** 3-column for cards (responsive to 1-column on mobile) -- **Max content width:** 1100px -- **Hero:** Full-width dark gradient, content centered, max-width 780px for headline -- **Dark sections:** Full-width background, content constrained to 1100px -- **Cards:** 1px border, 12px radius, subtle hover shadow - -## Motion -- **Approach:** Minimal-functional -- **Easing:** ease-out for entrances -- **Duration:** 500-700ms for scroll-triggered fade-ins -- **Patterns:** Fade-in + translate-y(8-20px) on scroll into view. No parallax, no bouncy entrances, no decorative animations. - -## Component Patterns - -### Buttons -- **Primary:** bg #1F6B3A, white text, 8px radius, 13-15px font, "Start Verifying →" -- **Ghost (on dark):** 1px border rgba(255,255,255,0.12), white/70 text, 8px radius -- **Ghost (on light):** 1px border #E7E4DD, #18181B text, 8px radius - -### Badges/Pills -- **Evidence pill:** green dot + "evidence" in JetBrains Mono 11px, #E8F5ED bg, #1F6B3A border -- **Claim pill:** red dot + "claim" in JetBrains Mono 11px, #FEF2F2 bg -- **Eyebrow badge:** uppercase 10.5px, #F5F4F1 bg, #E7E4DD border, #8A8F99 text - -### Hero Badge -- Dark translucent bg (rgba white 6%), 1px border (rgba white 8%), pill shape -- Green dot + JetBrains Mono 12px text - -### Code Block -- #18181B bg, 12px radius, 36-40px padding -- JetBrains Mono 13px, line-height 1.8 -- Syntax: keys #58A6FF, strings #4ade80, comments rgba(255,255,255,0.25) - -### Section Eyebrow -- 10.5px uppercase, tracking 0.08em, bold, Space Grotesk, #8A8F99 -- Always above the section title, 10-12px margin-bottom - -## A/B Test Versions - -Four versions sharing this design system, differing in copy and section order: - -| Version | Hero angle | Key differentiator | -|---|---|---| -| A (control) | Current copy — "Turn human claims into evidence" | Baseline measurement | -| B (outcome) | "Your meetings become verified actions. Automatically." | Outcome-focused, Odoo demo proof | -| C (role) | "AI that turns meetings into project docs, with proof." | Role-based cards (ERP/CRM, Agencies, Teams) | -| D (magic) | "Your meeting just flagged a risk, drafted mitigations, and contacted a supplier. Before it ended." | L1/L2/L3 escalation stories | - -## Source Documents -- Visual tokens: `docs/VISION.md` line 303 (locked palette + font) -- Full design system: `~/Github/knowledge/llm-wiki/wiki/Knowcap/knowcap-mockup-design-system.md` -- Positioning copy: `docs/POSITIONING.md` (three sentences for three surfaces) -- Strategy context: `docs/STRATEGY.md` (three-loop flywheel) -- StratDev Figma: `https://www.figma.com/design/zaWrwYbvwG9G5UpXowQEMq/Knowcap` - -## Decisions Log -| Date | Decision | Rationale | -|------|----------|-----------| -| 2026-05-25 | Created design system | /design-consultation based on VISION.md tokens + competitive research (10 products) | -| 2026-05-25 | Single accent (#1F6B3A green) | Green = verified = truth. No secondary accent. Color is rare and meaningful. | -| 2026-05-25 | JetBrains Mono for key claims | Makes claims feel like code contracts, not marketing copy. Unique in the space. | -| 2026-05-25 | Removed EU AI Act compliance badge | Product supports the requirements but no formal certification. Don't claim what you haven't audited. | -| 2026-05-25 | Removed fake stats + testimonials | A product about truth shouldn't have fabricated numbers on its landing page. | -| 2026-05-25 | Human confirmation = mechanism, not headline | Lead with outcomes (speed, actions, results). Verification is step 3, not the tagline. | -| 2026-05-25 | 4-version A/B test | Test outcome-first vs role-first vs show-the-magic vs current baseline | -| 2026-05-25 | Incorporated StratDev role-based layout | ERP/CRM Implementers, Agencies, Teams — better than generic personas | diff --git a/docs/README.md b/docs/README.md index e9f0a10..b7dabf5 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,27 +1,23 @@ -# docs/ — Knowcap marketing content +# docs/ — Knowcap website assets -Everything humans read in this repo. Mirrors the `docs/` pattern from the main `knowcap` repo, but here the content is brand + research + campaigns instead of architecture + governance + ops. +Website-specific assets only. All knowledge docs (brand, strategy, research, content) migrated to the **claude-knowcap brain** 2026-06-11. -## Layout +→ [claude-knowcap/knowledge/](https://github.com/Knowcap-V2/claude-knowcap/tree/main/knowledge) -| Folder | What | -|---|---| -| [`brand/`](./brand/) | DNA — VISION, POSITIONING, MOAT, STRATEGY, PRODUCT, personas, decisions, design explorations, legacy positioning | -| [`research/`](./research/) | Audits (SEO + GEO), competitor breakdowns, raw data CSVs | -| [`campaigns/`](./campaigns/) | StratDev agency briefs, paid-ad copy, landing-page experiments | -| [`content-pipeline/`](./content-pipeline/) | Blog drafts pre-publish, ideas, video briefs, marketing content plan | -| [`strategy/`](./strategy/) | GTM strategy + June 2026 GTM game plan | -| [`DESIGN.md`](./DESIGN.md) | Primary design system (cream + Space Grotesk) | -| [`DESIGN-E.md`](./DESIGN-E.md) | /e variant design system (brass + midnight forensic dossier) | - -## What's NOT here +## What's still here -- The live Next.js website code → `../app/` -- Shipped blog posts (Markdown rendered by Next.js) → `../app/content/blog/` -- Engineer docs (architecture, ops, governance, proposals) → [`Knowcap-V2/knowcap/docs/`](https://github.com/Knowcap-V2/knowcap/tree/main/docs) +| What | Where | +|---|---| +| Live Next.js website code | `../app/` | +| Shipped blog posts | `../app/content/blog/` | -## Cross-links +## What moved to claude-knowcap brain -- `feat()` PRs in the main `knowcap` repo cite `docs/brand/VISION.md` via the full GitHub URL pattern: `https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/VISION.md` -- `docs/research/competitors/read.ai/positioning.md` cites Knowcap's brand DNA via full URLs above -- `docs/campaigns/meta-paid-sprint.md` cites `docs/brand/legacy/` and `docs/content-pipeline/video/` via relative paths +| Was here | Now at | +|---|---| +| `brand/` (VISION, MOAT, POSITIONING, STRATEGY, PRODUCT, personas, decisions, design-explorations) | `knowledge/strategies/` · `knowledge/people/` · `knowledge/decisions/` · `knowledge/product/` | +| `research/` (audits, competitors, data) | `knowledge/topics/research/` | +| `campaigns/` | `knowledge/strategies/campaigns/` | +| `content-pipeline/` | `knowledge/content-and-features/content-pipeline/` | +| `strategy/` | `knowledge/strategies/` | +| `DESIGN.md`, `DESIGN-E.md` | `knowledge/product/` | diff --git a/docs/brand/MOAT.md b/docs/brand/MOAT.md deleted file mode 100644 index 2ad5b83..0000000 --- a/docs/brand/MOAT.md +++ /dev/null @@ -1,237 +0,0 @@ -# Knowcap Moat — why verification survives even at 100% AI accuracy - -Hassan-owned. The strategic foundation underneath [VISION.md](./VISION.md). Read this when somebody — a competitor, an investor, a developer, or your own doubt — asks "but won't AI just get good enough that human verification becomes obsolete?" - -**Updated:** 2026-05-25. Added Force 5 (market evidence across 15 products), Mem0 production audit data point, Glean reclassified from existential threat to narrative competitor. Prior research 2026-05-19 across model-reliability benchmarks (METR, SWE-bench, GAIA, OSWorld), lab statements (Anthropic, OpenAI, DeepMind), and regulatory analysis (EU AI Act, GDPR, FINRA, ESMA, CMS, ABA, HHS). - ---- - -## TL;DR - -The verification moat is NOT "we catch hallucinations." Three forces keep it alive regardless of how good AI gets: - -1. **Math** — multi-step agent workflows compound errors. 20 steps × 95% per-step accuracy = 36% end-to-end success. Checkpoints are arithmetic, not engineering. -2. **Security** — prompt injection is "unlikely to ever be fully solved" (OpenAI CISO Dane Stuckey, Dec 2025). Any agent reading untrusted content needs a trusted-fact substrate. -3. **Law** — regulators require human attestation as a non-delegable legal artifact. A 100%-accurate AI still cannot be the legal signatory. - -The moat is **statutory + structural**, not accuracy-bound. It gets STRONGER as AI gets more capable, because more capability means more regulatory pressure on human-in-the-loop requirements. - ---- - -## Force 1 — The math - -Frontier agent accuracy in May 2026 is dramatically better than 2024 but nowhere near "no verification needed": - -| Benchmark | Top score (May 2026) | What it means | -|---|---|---| -| SWE-bench Verified | 88.7% (GPT-5.5), 93.9% (Claude Mythos Preview) | Headline coding-task accuracy. Inflated by benchmark contamination. | -| SWE-bench Pro (contamination-free) | 45.9% | Reality. 48-point gap. | -| GAIA (real-world assistant) | 74.6% | Mid-difficulty multi-step tasks. | -| OSWorld (computer use) | 82% (Coasty) | Just crossed human baseline (72.36%). | -| Hallucination rates | 3.1%–19.1% | 3-8× better than 2024 (15-45%). Still measurably non-zero. | - -**The compounding problem:** in a multi-step agent workflow, per-step accuracy multiplies, not adds. - -| Per-step accuracy | 5-step success | 10-step success | 20-step success | -|---|---|---|---| -| 95% | 77% | 60% | **36%** | -| 99% | 95% | 90% | 82% | -| 99.9% | 99.5% | 99.0% | 98.0% | - -Even at hypothetical 99.9% per-step accuracy, a 20-step workflow still has a 2% catastrophic failure rate. For an agent that takes consequential actions (opens a PR, sends a client email, charges a card), 2% catastrophic failure rate is the difference between "tool" and "lawsuit waiting to happen." - -**Source:** Google Cloud's 2025 CTO retrospective explicitly identifies multi-step compounding as the dominant operational risk. arXiv MAKER paper on million-step zero-error agents demonstrates the engineering effort required to mitigate this with checkpoints. - -**Implication:** verified checkpoints (human-confirmed facts the agent can fall back on) are arithmetic necessities for any non-trivial workflow. This does not change as base models improve. - ---- - -## Force 2 — The security problem - -Prompt injection — both direct and indirect — is unsolved and getting worse. From the May 2026 threat landscape: - -- **OpenAI CISO Dane Stuckey (Dec 2025):** prompt injection is *"a frontier, unsolved security problem... unlikely to ever be fully solved."* -- **Indirect prompt injection in the wild:** +32% Nov 2025 → Feb 2026 (Help Net Security). -- **Real-world example:** Google Doc → coding agent → leaked dev secrets, zero user action required. -- **Replit incident, July 2025:** AI agent deleted production database during code freeze, then *fabricated* a recovery-impossibility story when caught. - -The pattern: any agent reading untrusted content (a meeting transcript with an adversarial speaker, an email with a malicious instruction, a document with embedded attack) can be deceived in ways that have nothing to do with model accuracy. The model is *being lied to*, not making a mistake. - -**Implication:** an agent acting in the real world needs a trusted-fact substrate it can rely on independent of what it reads in any single document. Knowcap's human-confirmed graph IS that substrate. Better models do not make this need go away — they make it more acute as agents take on higher-stakes actions. - ---- - -## Force 3 — The regulatory floor - -This is the durable one. Regulators require human attestation **not because AI is wrong**, but because **a natural person must be legally accountable.** A perfect AI still cannot be the signatory. - -### Hard legal requirements (human verification mandated by law) - -| Regulation | Jurisdiction | Effective | What it mandates | -|---|---|---|---| -| **EU AI Act Article 14** | EU | **Dec 2 2027** (deferred from Aug 2 2026 via the Digital Omnibus, ~May 2026) | Natural-person oversight on every high-risk AI system. Biometric identification requires TWO humans to confirm. | -| **GDPR Article 22** | EU + UK | In force | Right to human intervention on automated decisions with legal effect. UK Data (Use and Access) Act 2025 preserved the requirement. | -| **ESMA MiFID II Statement** | EU | May 2024 | "Investment firm decisions remain management's responsibility irrespective of whether taken by people or AI-based tools." Non-delegable. | -| **CMS Medicare Advantage Final Rule (CMS-4201-F)** | US | Jan 1 2024 | AI may *inform* but cannot *decide* coverage. Physician review required for adverse medical-necessity denials. | -| **HHS OCR Section 1557 Final Rule** | US | May 2024 | Patient care decision support tools (incl. AI) require covered entities to identify discriminatory variables and maintain human governance. | -| **ABA Formal Opinion 512** | US legal practice | Jul 2024 | Lawyers may not rely on AI outputs "without independent verification or review." AI cannot autonomously file or commit on behalf of a client. | - -### Strong contractual / audit expectations (verification mandated by liability) - -| Standard | Mandates | -|---|---| -| **FINRA Rule 3110 (Supervision)** | 2025 + 2026 FINRA Annual Regulatory Oversight Reports: AI does not change supervisory obligations. Member firms must show human review of AI recommendations before client delivery. | -| **SOX 404 ICFR attestation** | CEO/CFO sign under criminal penalty. Auditors are flagging algorithmic-control trail gaps. Human approval steps becoming de-facto required. | -| **SOC 2 Type II** | 2025 Deloitte data: 68% of SOC 2 auditors found AI control gaps; 41% issued qualified opinions. AI-drafted policies require human review evidence pack. | -| **ISO/IEC 42001:2023 (AI management systems)** | Clause 8 requires validation, change management, and human oversight controls. Becoming a procurement gate. | -| **Moffatt v. Air Canada (2024 BCCRT 149)** | Established at common law: companies are liable for everything their AI agent says. No "the bot did it" defense. | - -### Industries where verification is OPTIONAL (and the moat erodes) - -- Pure internal B2B productivity (Confluence pages, scheduling, dev tooling) -- Marketing copy generation, non-credit lead scoring -- Consumer convenience apps below GDPR Art. 22 "significant effect" threshold - -**This is the segment Knowcap explicitly does NOT sell to.** See [POSITIONING.md](./POSITIONING.md) anti-buyer section. - ---- - -## Force 4 — The composition layer Anthropic doesn't ship (added 2026-05-20) - -Anthropic owns the `SKILL.md` file format (open standard since Dec 2025) and the Skills runtime. Cursor, Goose, Microsoft, Stripe, Atlassian all consume it. Skills compose with MCP tools. - -**Anthropic does NOT ship:** -- An Instructions Hierarchy (how org/project/user context composes into the agent's system prompt before a Skill runs) -- A verified-fact substrate the Skill queries at runtime -- An audit log binding every Skill execution back to a named human confirmer -- A cross-org confirmation gate -- A Rules-mode layer for deterministic-cheap procedures alongside LLM-mode Skills -- A persona-tier composition (user role / escalation defaults / authorization scope) - -Knowcap ships all six. Every Knowcap `agents/{slug}.md` is a strict superset of `SKILL.md` — it exports to a standalone Anthropic Skill in any Skills-aware runtime, but the *Hierarchy stays on Knowcap servers* and the Skill consults it via MCP at runtime. - -**Why this is a moat, not a feature:** for Anthropic to ship the composition layer, they'd have to take a position on enterprise data semantics (what is an "org" vs a "project" vs a "user," what gets versioned where, who can edit what). That's a vertical-product opinion Anthropic deliberately avoids because they're the horizontal platform. The layer below the file format is open by design. **We sell into the gap.** - -See [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md) for the full architecture. - ---- - -## Why labs themselves never say "verification becomes unnecessary" - -We checked. From the major labs in 2025-26: - -- **Dario Amodei (Anthropic, Jan 2026 "Adolescence of Technology"):** AI writing "vast majority" of Anthropic production code; predicts 6-12 months to autonomous complex SWE. But explicitly: *"frontier AI systems are simply not reliable enough to power fully autonomous weapons."* 2026 goal is "almost never goes against the spirit of its constitution" — not *never*. -- **Sam Altman (OpenAI, Dec 2025 memo):** directed all teams to prioritize *"quality, speed, and reliability above everything else."* Publicly worried about unauthorized agent behaviors. 2026 framing: agents as "brilliant interns" — not autonomous operators. -- **Demis Hassabis (DeepMind, 2026):** AGI in "~5 years," requires "one or two breakthroughs on the level of AlphaGo." Expanding data + compute alone is *not* enough. - -**Across all four labs, no public commitment to a date when human verification becomes unnecessary.** The hedging is the signal. - ---- - -## TAM implication - -Based on Gartner's $644B GenAI spending forecast (2025) and McKinsey's State of AI sector breakdown: - -- ~55–65% of enterprise AI spending sits in industries where regulation, audit, or liability law mandates human verification — not because models are imperfect, but because a human signature is the regulated artifact -- ~35–45% sits in unregulated productivity workflows where the moat erodes as models improve - -**Knowcap targets the larger slice.** [POSITIONING.md](./POSITIONING.md) buyer profile (Odoo partners → regulated verticals → horizontal) is constructed to land squarely in the durable 55-65%. - ---- - -## The framing risk (this is the only thing we have to manage) - -The moat survives. The *framing* erodes if we let it. - -- ❌ **Weakens every quarter:** "We catch AI hallucinations." (Gets less impressive as models improve.) -- ✅ **Strengthens every quarter:** "We are the attestation infrastructure for regulated AI agents — auditable under EU AI Act Article 14." (Gets more impressive as agents take on higher-stakes actions and regulation tightens.) - -**Sales must use the second framing, not the first.** When a prospect asks "but Claude is getting really accurate, why do we need verification?" the answer is: - -> *"Accuracy isn't the issue. EU AI Act Article 14 / FINRA / your auditor requires a human signature on every consequential AI action — independent of how accurate the model is. We give you that signature, queryable by your agents, with full provenance. When your auditor asks 'who confirmed this fact?' we have a name, a timestamp, and the source clip."* - -This framing is timeless. It gets MORE valuable as agents become MORE capable, because regulation responds to capability. - ---- - -## Force 5 — Market evidence (added 2026-05-25) - -Research across 15 products in 4 layers found unanimous absence of human verification: - -| Layer | Products researched | Human verification? | -|---|---|---| -| Meeting notetakers | Fireflies, tl;dv, Otter, Sembly, Circleback, Read.ai | 0 of 6 | -| Enterprise knowledge | Glean ($7.2B), Microsoft Work IQ | 0 of 2 | -| AI memory infra | Mem0, Zep/Graphiti, Letta, Cognee | 0 of 4 | -| Platform AI | Google Workspace Intelligence, NotebookLM, Granola ($1.5B) | 0 of 3 | - -The gap is not a missing feature. It is a missing architectural primitive. Adding verification to Fireflies' 200 fire-and-forget Skills, or to Otter's 25M-user index-everything pipeline, or to Glean's enterprise graph, would require fundamental architectural changes — 12-18 months of retrofit, not a feature flag. - -Mem0's production audit (GitHub #4573) found 97.8% of AI-extracted memories were junk without human review — restated prompts, hallucinated profiles, transient state. This is the failure mode human verification exists to prevent. - ---- - -## The 90-day clock (what could still kill us) - -The risk is not "AI gets too good." The risk is not any single competitor either. Glean ($7.2B, Series F May 2026) is a **narrative competitor**, not an existential threat — different product ($80K+/yr enterprise search), different buyer (Fortune 2000 CIOs), no meeting-first capture, no Arabic/MENA, no cross-org confirmation. They could rebrand for EU AI Act compliance, but they'd be selling to a buyer we don't target. - -The existential risk is not any single competitor. It is shipping too slowly for the MENA mid-market buyers who are ready now. - -**The window (revised 2026-05-29):** EU AI Act Art 14 enforcement was deferred to Dec 2 2027, so the near-term forcing functions are **Saudi PDPL (enforced since Sep 2024)** and **GDPR Article 22 / CJEU SCHUFA** — both in force now. Anchor the "why now" there; the EU AI Act remains a 2027 tailwind. See [the 2026-05-29 re-adjudication](./decisions/2026-05-29-mena-council-readjudication.md). - -**What we have to ship to win the window:** - -1. ~~Fix the 3 `review_status` ignore-sites~~ **DONE 2026-05-12 via PR #305.** Confirmed: `memoryService.ts:372-375` filters by `review_status` and sorts by `importance DESC`; LLM prompt tags every memory via `tagFor()` at lines 422/432/442/452; MCP `search_memories` accepts a `status` array. The verification gate is real in production for the core memory path. (See `project_knowcap_evidence_gap_in_prod`.) -2. **Ship the `confirmation_source` schema split** — add a column to `project_memories` distinguishing `human_confirmed` from `auto_confirmed_rule_v1`. Without this, [VERIFICATION-UX.md](./VERIFICATION-UX.md) Mechanism 2 (rule promotion) cannot ship honestly. Migration + server + UI. **Target: 30 days.** -3. ~~Add MCP `verification_strictness` convenience parameter~~ **DONE 2026-05-19 via knowcap-mcp PR #7.** Agents now call `search_memories(verification_strictness='human_only')` and the MCP guarantees only `confirmed+edited` memories return. `rule_auto_ok` is identical today and will expand when `confirmation_source` ships (item 2). -4. **Ship the Odoo lighthouse demo** — meeting → human-confirmed memory → **Odoo task** (the auto-generated SH **PR** version is killed — ≈0% built; see [2026-05-29 decision](./decisions/2026-05-29-mena-council-readjudication.md)). **Target: on demo-readiness.** -5. **Publish the "Knowcap and EU AI Act Article 14" technical brief.** Hassan's voice; technical depth; positioned for compliance officers Google-searching the regulation. **Target: 2026-06-15.** -6. **Land 3-5 regulated-vertical pilot customers** with full audit-trail demos by 2026-09-30. - -If we hit these six, the moat is in production with proof points by the time the EU AI Act enforcement window peaks. If we miss them, the MENA mid-market buyers who are ready now will find workarounds — and workarounds calcify into habits we can't displace. - ---- - -## What this moat is NOT - -- **Not a feature checklist.** "We have a confirm button" is not a moat. The moat is the *contract* — that nothing flows downstream to an agent without a named human attestation, end-to-end through the schema, the chat loader, the RAG layer, and the MCP. -- **Not vendor-lock through data hoarding.** We don't sell verification by trapping data. We sell it by making the audit trail uniquely valuable when an auditor/regulator/court is the reader. -- **Not pure compliance theater.** A "verified" badge that anyone can click "confirm all" on is worthless. See [VERIFICATION-UX.md](./VERIFICATION-UX.md) for the hard rules that keep this real. - ---- - -## Sources (for the verification-survives-AI-accuracy claim) - -Research conducted 2026-05-19 across: - -**Reliability trajectory:** -- METR Task-Completion Time Horizons (4.3-month doubling, post-2023) -- SWE-bench Verified leaderboard (Marc0) -- SWE-bench Pro contamination-free benchmark (Morph) -- UC Berkeley RDI on trustworthy benchmarks -- OSWorld 2026 results (Coasty) -- Digital Applied 2026 hallucination study; Suprmind hallucination benchmarks - -**Lab statements:** -- Dario Amodei, "The Adolescence of Technology" (Jan 2026) -- Sam Altman memo via Analytics Insight (Dec 2025) -- Demis Hassabis 36Kr interview (2026) -- OpenAI CISO Dane Stuckey on prompt injection (Dec 2025) - -**Regulatory floor:** -- EU AI Act Article 14 official text -- EU AI Act 2026 compliance analysis (Holland & Knight, DLA Piper, Trilateral Research) -- GDPR Article 22; ICO UK guidance + Data (Use and Access) Act 2025 -- ESMA Public Statement on AI and investment services (May 2024) -- FINRA 2025 + 2026 Annual Regulatory Oversight Reports -- CMS Medicare Advantage AI coverage determinations FAQ -- HHS OCR Section 1557 patient care decision support tools rule -- ABA Formal Opinion 512 -- Moffatt v. Air Canada (BC Tribunal 2024) -- ISO/IEC 42001:2023 AI management systems standard -- McKinsey State of AI 2025 sector breakdown - -**Failure case studies:** -- Replit production DB deletion (July 2025) -- Cursor AI support bot fabricated login policy (April 2025) -- Air Canada chatbot liability ruling (2024) diff --git a/docs/brand/POSITIONING.md b/docs/brand/POSITIONING.md deleted file mode 100644 index dace610..0000000 --- a/docs/brand/POSITIONING.md +++ /dev/null @@ -1,224 +0,0 @@ -# Knowcap Positioning - -Hassan-owned. The outward-facing answer to "what is Knowcap and who is it for." Sales, marketing, landing pages, cold outreach, and partner conversations all pull from this doc. - -**Updated:** 2026-05-19. Commitment-centric thesis added 2026-06-04; folded into the brand docs 2026-06-08. - ---- - -## The commitment-centric thesis (org model — 2026-06-04) - -> **An organization is a web of commitments — internal (employee↔manager) and external (client, partner, supplier). Every commitment carries risk. Risk is mitigated by decisions and tasks. Tasks fulfil commitments. Notes are the verified substrate.** -> -> Knowcap captures every commitment your org makes — to your team and to your clients — flags the risks against them, and turns the mitigation into tracked tasks. - -This is the product's center of gravity. The three positioning sentences below are how you SAY it in different rooms; the org model above is WHY it's true. - -Full thesis (mini blog + LinkedIn draft): [`docs/content-pipeline/drafts/commitment-thesis.md`](../content-pipeline/drafts/commitment-thesis.md). The memory-category model it implies (Decision · Task · Commitment · Risk · Note): [`memory-ontology.html`](./memory-ontology.html) + [VISION.md → "The 5 Layer-1 categories"](./VISION.md). - ---- - -## The three sentences (use the right one in the right place) - -| Surface | Sentence | -|---|---| -| **VISION.md, internal docs, investor decks, formal sales conversations** | *"Knowcap is the trust layer for AI agents — every fact they act on is confirmed by a named human, with a full audit trail."* | -| **Landing page hero, cold email subject, demo opener, ProductHunt** | *"Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true."* | -| **Footer, X bio, conference badge, 12-word brand line** | *"Knowcap is verified knowledge for AI agents. Humans confirm. Agents act."* | - -Same thesis, three voices, three audiences. **Do not invent new sentences for the same surface.** If you find yourself rewriting these, propose the change in a PR against this doc first. - ---- - -## What Knowcap IS — affirmative - -> **Knowcap is the verified-fact + instructions substrate Anthropic-compatible Skills run on. Skills are the procedure; Knowcap is the truth.** - -We are NOT a competitor to Anthropic Skills — **we are a consumer + superset of their spec.** Every Knowcap `agents/{slug}.md` Playbook is exportable to a standalone Anthropic Skill folder. What Anthropic doesn't ship — and what we own: - -- The Instructions Hierarchy (`organization.md → projects/{slug}.md → users/{slug}.md`) that composes ABOVE the Skill body -- The verified-fact substrate the Skill queries at runtime (Knowcap MCP with `verification_strictness`) -- The audit log binding every Skill execution back to the named human confirmer -- The cross-org confirmation gate that controls which Skills can fire -- The deterministic **Rules** (routing/filing) layer running alongside LLM-mode **Skills** (vocabulary updated 2026-05-29 — "Playbooks" retired; see [`decisions/2026-05-29-agent-skills-routines-architecture.md`](./decisions/2026-05-29-agent-skills-routines-architecture.md)) - -See [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md) for the architecture. - ---- - -## Categories we explicitly stay out of - -| Category | Who owns it | Why we don't fight | -|---|---|---| -| Meeting notetakers | Read.ai, Otter, Fathom, Granola, Fireflies, Tactiq, Jamie | Commodity. Top complaint is summary accuracy (model upgrades solve it). Bot fatigue is the #1 buyer pain. Distribution + velocity war we lose. | -| Enterprise knowledge graph | Glean ($7.2B), Microsoft Graph, Notion AI Q&A | $300+/user/mo price points, 3-year SSO/ACL/SOC2 head start, Glean's Fellow-meeting ingest shipped Jan 2026. We layer on top, not against. | -| AI memory infrastructure | Mem0, Zep/Graphiti, Letta, Cognee, Cloudflare Agent Memory | They're plumbing, we're a product. Their typed-edge models are architecturally close, but they have no UX and no end-user buyer. | -| Skills runtime | Anthropic, OpenAI (quietly), Cursor, Goose, Atlassian | Platform-owned standard since Dec 2025. We consume it, ship Skills FOR it, do NOT compete with the runtime. | -| Pure summary accuracy | Every AI lab | Solved by model upgrades. *"We catch hallucinations"* is a feature that ages out. | - ---- - -## The stack — where Knowcap sits - -``` -Layer 5: AGENT RUNTIME Anthropic Skills, Claude Desktop, Cursor, Goose, OpenAI Agents - ↑ invokes -Layer 4: SKILL / PLAYBOOK agents/{slug}.md (Anthropic-Skill-compatible) - ↑ composed from -Layer 3: INSTRUCTIONS HIERARCHY organization.md / projects/*.md / users/*.md ← KNOWCAP OWNS - ↑ grounded in -Layer 2: VERIFIED FACTS human-confirmed, audit-trailed, MCP-served ← KNOWCAP OWNS - ↑ extracted from -Layer 1: AI MEMORY + RAG vectors, embeddings, retrieval (Mem0/Zep below) - ↑ produced from -Layer 0: CAPTURE + INGEST recordings, docs, emails, Telegram, WhatsApp -``` - -Layer 5 (runtime) is Anthropic + the runtime ecosystem. Layer 4 (file format) is Anthropic's spec, with our extension fields. **Layers 2-3 are Knowcap's territory** and nobody else ships them as a composable unit. Layers 0-1 are downstream concerns we don't compete on. - -The buyer pitch: *"Anthropic gives agents skills. We give those skills an org, a project, a user, and verified facts. Without us, your skills hallucinate the company context. With us, they run on confirmed truth."* - ---- - -## Real competition — who to actually watch - -### Tier 1 — closest threats (active monitoring) - -**Glean** ($7.2B valuation, $150M Series F May 2026) -- Shipped Fellow meeting integration Jan 2026 — meeting transcripts now ingest as docs in their Enterprise Graph -- Their May 2026 launch added "agents that proactively manage tasks" -- **What they don't have yet:** human-verification primitive, `review_status` schema, cross-org confirmation network -- **How they could attack us:** ship a "verified" pill on summaries + an EU AI Act compliance checkbox. ~1 quarter of work for them. -- **Our defense:** ship the verification gate end-to-end + own the regulated-vertical buyer language before they reframe. - -**Zep / Graphiti** (open-source, well-funded) -- Their typed-edge model with explicit contradiction detection (`t_invalid`) and temporal validity is architecturally our closest twin -- **What they don't have:** a meeting-capture UX, end users, vertical positioning. They're plumbing. -- **How they could attack us:** someone wraps Graphiti in a meeting-recorder UX and sells it. Could happen in a quarter. -- **Our defense:** the verticalized agent-action layer (Odoo SH PR, financial advisor compliance log, legal redline) is what end-buyers pay for. Plumbing alone doesn't compete with a product. - -**Tana** (Current launched March 2026) -- Meetings + collaborative knowledge graph + agents + bug/decision/action-item capture during the conversation -- Closest *spiritual* sibling — they think about the world the way we do -- **What they don't have:** the human-attestation primitive as a first-class entity; enterprise compliance positioning; org-scoped ACL story -- **How they could attack us:** add a "verified" badge + an enterprise tier. Possible but they have PKM brand inertia (perceived as a personal tool). - -### NON-competitors (we layer on these, NOT against them) - -**Anthropic Skills** (open standard since Dec 2025, adopted by Microsoft, Cursor, Goose, Stripe, etc.) -- They own the `SKILL.md` file format and the Skills runtime -- We are a strict superset of their spec — every Knowcap `agents/{slug}.md` is exportable to a standalone Skill folder -- Our position: *"Knowcap-authored Skills are the only ones that come with verified-fact provenance and an Instructions Hierarchy. Anthropic ships the rails; we ship the trust."* -- Stripe-Visa analog: Stripe didn't compete with Visa, they built the developer-grade layer above the rails - -### Tier 2 — distraction zone (don't waste cycles) - -**Read.ai** — the company Hassan was worried about 2026-05-19. Reality: they ship a notetaker with MCP, Ask Read, an agentic suite (Ada), and CRM writes. **They are good at being a notetaker.** They are not architecturally close to the verification thesis. Their disclaimer "outputs may require human review" is a disclaimer, not a primitive. We don't fight them; we fight Glean. - -**Otter.ai** — pivoted in April 2026 to "Conversational Knowledge Engine" (cross-meeting search via MCP). Same category as Glean now. Same defense applies. - -**Mem0 / Letta** — infra plays, sold to developers, not end users. We integrate with them or compete on the application layer, not the infra layer. - ---- - -## Buyer profile - -### Buyer 1 — Odoo partners (Phase 1, now → 12 months) - -**Who they are:** boutique-to-mid-market consulting firms (10–200 employees) that implement and customize Odoo for clients. SMEtools is one. Hassan has insider distribution. - -**Their pain:** -- Every implementation hinges on what was agreed in client meetings (SOW scope, change requests, go-live decisions) -- Litigation risk when client disputes "but you said this was in scope" -- Implementation devs spend hours translating meeting decisions into Odoo modules / Studio configs -- Audit trail for client billing is informal (email threads, partner WhatsApp groups) - -**What we sell them:** -- Meeting → human-confirmed scope decision (client confirms too, via cross-org bridge — Loop 2) -- Confirmed scope decision → auto-generated Odoo SH PR draft for the partner's dev team to review -- Cross-org confirmation rail = bulletproof audit trail for billing disputes - -**Pricing implication:** $50-200/seat/month range. Cross-org confirmation can be charged on both sides (partner + client get value). - -**Why this is the right beachhead:** Hassan's distribution + clear lighthouse demo + code-shaped work product + adjacent path to next vertical (accounting, then full regulated). - -### Buyer 2 — Regulated knowledge work (Phase 2, month 6 → year 2) - -**Who they are:** financial advisors (RIA firms, IFA practices, wealth managers), boutique-to-mid-market law firms, healthcare admin teams (not clinical), SEC-registered investment firms, compliance officers at mid-size companies. - -**Their pain:** -- Their regulator REQUIRES human attestation on AI-assisted decisions (FINRA Rule 3110, ESMA MiFID II, ABA Op. 512, CMS MA Final Rule) -- They already pay $30–100/user/month for compliance-grade tooling -- AI is creeping into their workflows but they have no audit-defensible way to use it -- Saudi PDPL (enforced Sep 2024) + GDPR Article 22 are the in-force forcing functions today; EU AI Act Article 14 is deferred to Dec 2 2027 (a 2027 tailwind, not a 2026 deadline) - -**What we sell them:** -- Every fact AI acts on is confirmed by a named human, signed, timestamped to source, audit-trailed -- "Compliance-attested AI" tier of agents — only confirmed facts as inputs, full lineage on every action -- Document the audit-defense story explicitly (EU AI Act Article 14, GDPR Article 22, etc. — see [MOAT.md](./MOAT.md)) - -**Pricing implication:** $100–500/seat/month range. Compliance buyers pay 5-10x what productivity buyers pay. - -**TAM context:** ~55-65% of enterprise AI spending sits in industries where the human signature is the regulated artifact. This is the bulk of the addressable market for Knowcap. - -### Anti-buyer — pure productivity workflows - -**Who they are:** founders, PMs, sales reps, marketing teams looking for "better meeting summaries." - -**Why we do NOT sell to them:** -- The verification UX is friction they don't value -- Their #1 want is accurate summaries + CRM sync — that's a Read.ai / Granola / Otter sale -- Lifetime value is low ($15-40/seat); churn is high -- They are the segment most exposed to "AI gets better → moat erodes" — exactly the customers we don't want - -**If a productivity buyer approaches us:** politely refer them to Granola or Fathom. Tell them we'll be ready when their compliance officer is. - ---- - -## What's shipped today vs aspirational tomorrow - -Sales must not promise vapor. The matrix below is the source of truth for what to demo and what to caveat. - -| Feature | Status (2026-05-19) | What sales can say | -|---|---|---| -| Meeting capture (Meet, recordings) | Shipped | "We capture every meeting" | -| Visual transcription + OCR + speaker ID | Shipped | "We extract from visuals + audio + speakers" | -| Claim extraction (5 categories) | Shipped | "We classify every memory into 5 actionable categories" | -| Pending → Evidence confirmation gate | Shipped | "Humans confirm each claim before it's used" | -| `review_status` enforced in chat-context loader + LLM prompt tagging + MCP filtering | **Shipped 2026-05-12** (PR #305) | "Your agents only see human-confirmed facts via MCP; the chat sorts evidence ahead of unverified claims" | -| RAG transcript-chunk retrieval respects `review_status` | **Intentionally not wired** | RAG operates on source chunks, not memories. Memories flow through the verification-respecting loader. Not a gap. | -| `confirmation_source` schema split (human vs rule-auto) | **Not shipped** | Roadmap. Required before sales can promise "auto-confirmed rules with audit trail." 30-day target. | -| MCP `verification_strictness` convenience parameter | **Shipped 2026-05-19** (knowcap-mcp PR #7) | "Your agents query `search_memories(verification_strictness='human_only')` and we guarantee they only see human-confirmed facts." | -| Typed edges (`mitigated_by`, `superseded_by`, etc.) | **Not shipped** | DO NOT PROMISE. Aspirational; target Sprint 3. | -| Instructions Hierarchy (org / project / user) | In progress | "Coming May 23" | -| Knowcap MCP for external agents | Shipped | "Your agents query our verified facts via MCP" | -| Cross-org confirmation (Parties) | Partial UI | "Pilot soon" — not for general sales | -| Odoo SH PR lighthouse demo | **Not built** | DO NOT DEMO yet. Target: 2026-07-31. | -| Agents marketplace | **Not built** | "Year 2 direction" — see [STRATEGY.md](./STRATEGY.md) loop 3 | -| Mobile app | **Not built** | "Post-launch direction" | - -**Rule:** if a feature is not in the "Shipped" column, sales DOES NOT lead with it. We can mention aspirational features in roadmap context, but a buyer must never see a demo of vaporware. - ---- - -## The compliance window (revised 2026-05-29) - -EU AI Act Article 14 enforcement was **deferred from Aug 2 2026 to Dec 2 2027** (Digital Omnibus, ~May 2026), so it is a 2027 tailwind, not a 2026 deadline. The in-force forcing functions to sell on **now** are **Saudi PDPL** (enforced Sep 2024 — explicit right to human intervention) and **GDPR Article 22 / CJEU SCHUFA** (a rubber-stamp human is legally insufficient — sharper than Art 14 ever was). - -**Our positioning move:** -- Publish a "human-in-the-loop attestation under Saudi PDPL + GDPR Article 22" technical brief on [knowcap-marketing](https://github.com/Knowcap-V2/knowcap-marketing) by 2026-06-15 -- Add "human attestation, audit-ready" copy to the landing page hero by 2026-06-30 -- Outbound to MENA Odoo-partner + regulated networks first; EU RIA / law firm / fractional CFO outreach as a parallel track - -**The headline:** while Read.ai and Glean sell "summaries" and "search," Knowcap sells "audit-ready human confirmation infrastructure" — *attestation infrastructure for regulated AI agents*, never "we catch hallucinations." - -See [the 2026-05-29 re-adjudication](./decisions/2026-05-29-mena-council-readjudication.md). - ---- - -## What to do with this doc - -- **Sales:** memorize the three sentences, the anti-positioning, the buyer profiles. Refer to the shipped-vs-aspirational matrix every time you describe a feature. -- **Marketing:** every landing page, email, and content piece must use one of the three sentences verbatim. Anti-positioning shows up in the "what we don't do" section of any long-form piece. -- **Devs:** if your PR introduces a feature, check it against the buyer profile — which buyer is this for? If neither, raise it with Hassan before shipping. If you can't fit it under one of the three sentences, the feature is in the wrong product. -- **Hassan:** edit this doc when positioning shifts. Edits propagate downstream — sales and marketing read here first. diff --git a/docs/brand/PRODUCT.md b/docs/brand/PRODUCT.md deleted file mode 100644 index 21af006..0000000 --- a/docs/brand/PRODUCT.md +++ /dev/null @@ -1,37 +0,0 @@ -# Product - -## Register - -brand - -## Users - -Odoo implementation partners (the beachhead), agencies, multi-company founders, and consulting/regulated teams who run client projects out of meetings. Their context: they are deciding whether it is safe to put an AI agent between their meetings and real client work. The job to be done is convincing themselves that an agent will act on confirmed facts, not on whatever it thought it heard, and that they can prove what it did after the fact. - -## Product Purpose - -Knowcap is the trust layer for AI agents. It captures meetings, screen sessions, and documents, turns them into a single verifiable project memory where every durable claim is confirmed by a named human, and then lets agents act only on what has been verified, leaving a full audit trail. The landing page succeeds when a visitor leaves believing this is the one where humans confirm before agents act: "AI that only acts on truth." - -## Brand Personality - -The voice of a record-keeper, not a hype startup. Three words: exacting, official, calm. Authoritative without being corporate; confident enough to show the evidence rather than assert outcomes. Serious and trustworthy, in the register of a legal brief or a lab notebook, never playful, never "AI magic." - -## Anti-references - -- Generic SaaS landing pages: gradient-mesh hero, rounded-icon feature grid, vague "supercharge your workflow" copy. -- Playful startup illustration style and mascot energy. -- tana.inc as an anti-positioning reference (per DESIGN.md): we are infrastructure for truth, not a power-user toy. -- "AI magic" hand-wave tone that asks for trust without earning it. -- For Version E specifically: the cream + Space Grotesk industrial-minimal system shipped in versions A through D. Version E exists to test a deliberately different visual point of view against that hand-built system, so it must not converge back toward cream-and-Space-Grotesk. - -## Design Principles - -1. **Show the evidence, do not claim it.** The page should feel built out of verified records, not marketing assertions. Proof is a visual material, not a bullet point. -2. **Outcomes are the headline, human confirmation is the mechanism.** Lead with what teams get (velocity, delivered projects, fewer tickets, faster onboarding). Verification is how it works, step three, never the tagline. -3. **Do not claim what you have not audited.** No fabricated stats, no certifications the product has not earned. A product about truth cannot have invented numbers on its own page. -4. **Authority through precision, not decoration.** Confidence comes from exact typography, deliberate spacing, and restraint, not from effects. -5. **Emphasis is rare and means one thing.** When the page marks a word or a value, the mark reads as "verified." Color and highlight are scarce so they stay meaningful. - -## Accessibility & Inclusion - -Target WCAG 2.1 AA. Body text contrast >= 4.5:1, large text >= 3:1. Full keyboard navigation with visible focus indicators on every interactive element. All motion has a `prefers-reduced-motion` fallback (crossfade or instant). Real alt text on every image. No known assistive-tech-specific user requirements documented beyond standard AA. diff --git a/docs/brand/README.md b/docs/brand/README.md deleted file mode 100644 index ed4fd3f..0000000 --- a/docs/brand/README.md +++ /dev/null @@ -1,20 +0,0 @@ -# Brand - -Knowcap brand DNA — vision, positioning, strategy, voice, personas, decisions, design explorations. - -## Canonical source of truth - -These are the single-canonical versions of strategy/brand/positioning. The `knowcap` (main app) repo links here from feat() PR bodies via full GitHub URL. - -| File | What | -|---|---| -| `VISION.md` | Product vision, trust-layer thesis, anti-positioning | -| `POSITIONING.md` | Three sentences, buyer personas, anti-positioning, sales gate | -| `MOAT.md` | Why verification survives even at 100% AI accuracy | -| `STRATEGY.md` | Three-loop flywheel, beachhead sequencing | -| `PRODUCT.md` | Brand register, voice, design principles | -| `personas/` | ICP research — MENA SME landscape, persona segmentation | -| `decisions/` | Strategic council outcomes, re-adjudications | -| `design-explorations/` | v3 visual variants (library, operator, operator-light, quarterly) | -| `legacy/` | Pre-pivot positioning and ICP segments — historical, not current truth | - diff --git a/docs/brand/STRATEGY.md b/docs/brand/STRATEGY.md deleted file mode 100644 index 37531af..0000000 --- a/docs/brand/STRATEGY.md +++ /dev/null @@ -1,229 +0,0 @@ -# Knowcap Strategy — the three-loop flywheel - -Hassan-owned. Lives next to [VISION.md](./VISION.md). Read this when you're about to build something and want to know **why** it gets built before **what** gets built. - -**Updated:** 2026-05-19. - ---- - -## TL;DR - -Knowcap runs three flywheels on one substrate. Each spins at a different speed. The first ships now. The second turns the product into a network. The third makes it a platform. - -> The substrate is the **org's verified-knowledge graph + named human confirmations over time.** Same data asset, three compounding monetization patterns. - -Comparable companies that ran this play: Salesforce (CRM record → AppExchange), Stripe (payment record → Radar + Treasury + Atlas), Shopify (commerce record → Apps + Capital + Payments). They didn't win with a single advantage — they won by stacking three flywheels on one asset. - ---- - -## The substrate, precisely: a web of commitments - -The "verified-knowledge graph" the three loops spin on isn't an abstract pile of facts. It's a **web of commitments** — every promise the org makes, internal and external. Commitments carry risk; risk is mitigated by decisions and tasks; tasks fulfil the commitments; notes are the verified facts it all stands on. That's the Layer-1 ontology (see [VISION.md → "The 5 Layer-1 categories"](./VISION.md) and [POSITIONING.md](./POSITIONING.md)). - -Why it matters for the flywheel: a **commitment has a counterparty** — the client, supplier, or manager it was made to. That counterparty is exactly who Loop 2 pulls onto Knowcap to confirm the shared commitment. The commitment ontology is what makes the cross-org confirmation network (Loop 2) inevitable rather than bolted-on. - ---- - -## Loop 1 — Within-org capture deepening - -**Spins from customer #1. Lowest ceiling. Fastest to start.** - -``` -employee captures a meeting - ↓ -agents act on confirmed claims (PR generated, email drafted, audit logged) - ↓ -employee sees ROI → invites another employee → captures more meeting types - ↓ -more confirmed facts → agents become smarter on this org's vocabulary, decisions, rules - ↓ -rule promotion: more confirmations → more auto-rules → less manual review → more capture - ↓ - LOOP -``` - -This is the **Slack-style intra-org viral.** One customer becomes 5 seats, becomes 50 seats. The compounding asset within the org: every confirmed fact makes the next agent run smarter on that org's specific vocabulary, decisions, and rules. - -**When this loop is healthy:** seat count per org grows month-over-month without targeted upsell motion. - -**Failure mode:** if employees can't get through their daily verification queue, capture slows and the loop breaks. See [VERIFICATION-UX.md](./VERIFICATION-UX.md) for why we must NOT solve this with a "confirm all" button (that breaks the moat instead of the loop). - ---- - -## Loop 2 — Cross-org confirmation network - -**Spins around customer #50–100 once supply-chain density emerges. Network-effect ceiling.** - -``` -Odoo partner uses Knowcap - ↓ -they want their CLIENT to confirm shared memories (e.g. SOW scope decision) - ↓ -they invite the client to confirm from their side - ↓ -client is now on Knowcap with a single shared memory - ↓ -client's NEXT supplier also wants confirmation → second org bridges in - ↓ -each new bridge increases value of being on Knowcap for everyone already on it - ↓ - LOOP -``` - -This is the **LinkedIn / DocuSign network effect.** Single-tenant tools cannot enter this loop. Knowcap enters because verified facts have *counterparties* — clients, suppliers, regulators, auditors — and each of them benefits from being on the same confirmation rail. - -**Concrete first instantiation (Odoo partners):** -- Hassan's SMEtools confirms a scope decision from a client meeting -- The client receives a single invitation: "confirm this SOW change from your side" -- Client clicks, signs in, confirms — now there's a two-sided verified fact -- Three months later the client uses Knowcap with their accountant for the year-end audit -- Now the accountant is on Knowcap. And so on. - -**When this loop is healthy:** % of confirmed memories that are *two-sided* (counterparty also confirmed) grows month-over-month. Cross-org bridges per active org grows. - -**Why this is the existential bet:** -- Loop 1 alone makes Knowcap a really good tool. Loop 2 makes it uncopyable. Glean, Read.ai, Otter are all single-tenant by design — they can't add this without rewriting their data model. -- The first 100 paying orgs are Loop 1 customers. Orgs 101-1,000 are pulled in by Loop 2. -- The product spec for Loop 2 is *already in the mockup* (Persons as cross-org confirmation surface — renamed from "Parties" 2026-05-20) — we just have to ship and instrument the viral mechanic. - -**Target:** Loop 2 instrumented and visible in metrics by month 12. - ---- - -## Loop 3 — Vertical Packs marketplace (reframed 2026-05-20) - -**Spins around customer #500–1,000 when developer audience reaches critical mass. Highest revenue ceiling.** - -The unit of distribution is a **Vertical Pack** — a bundle of: -- `organization.md.template` — the vertical's vocabulary, category semantics, tone -- `projects/.template` — the per-project glossary template for engagements in this vertical -- `users/.template` — role-based user-tier templates (`delivery_lead`, `compliance_officer`, `partner_dev`, etc.) -- 5-10 `agents/*.md` Playbooks — pre-built procedures specific to this vertical -- Optional `scripts/` — bundled deterministic helpers a Playbook can shell out to - -**Example packs (sequenced per the beachhead plan below):** - -| Pack | Anchor Playbooks | -|---|---| -| **Odoo Partner Pack** | `odoo-scope-to-pr`, `client-status-update`, `sow-confirmation-followup`, `module-changelog-from-meeting`, `support-ticket-triage` | -| **Financial Advisor Pack** | `client-meeting-compliance-log`, `mifid-suitability-record`, `quarterly-review-prep`, `escalation-to-supervisor`, `rmd-reminder-draft` | -| **Legal Practice Pack** | `matter-memo-draft`, `contract-redline-triage`, `privilege-flag-on-confirmation`, `client-update-letter`, `time-entry-from-meeting` | -| **Healthcare Admin Pack** | `prior-auth-packet`, `denial-appeal-draft`, `cms-compliance-log`, `patient-callback-prep`, `incident-report-intake` | - -``` -Knowcap has N orgs × verified-fact graphs accessible via MCP - ↓ -Knowcap (Year 1-2) ships first-party Vertical Packs — Odoo Partner first - ↓ -Year 2-3: third-party developers ship vertical Packs (Spellbook → Knowcap Legal Pack, -specialized firms → niche packs); Knowcap takes 15-30% revenue share - ↓ -Each Pack also exports as standalone Anthropic Skill folders — usable in -Claude Desktop / Cursor / Goose WITHOUT a Knowcap subscription, BUT the -exported Skills can only reach verified facts if the user also has Knowcap MCP wired in - ↓ -The verified-fact gate is what gives a Knowcap Pack the "audit-certified" tier -that a vanilla Anthropic Skill folder cannot claim - ↓ -each new Pack pulls more vertical buyers; each new buyer makes Pack-building attractive - ↓ - LOOP (Salesforce AppExchange / Shopify Apps / Stripe Apps model) -``` - -This is the **platform flywheel.** Highest revenue ceiling — Shopify Apps does ~$1B/year on top of Shopify itself; Salesforce AppExchange does similar. Knowcap's twist: every Pack is BOTH a Knowcap-internal install AND a portable Anthropic Skill folder. Buyers can deploy in either runtime. - -**The Knowcap-specific advantage:** because we have the verification primitive AND the Instructions Hierarchy above the Skill body, a Knowcap-authored Pack delivers something a vanilla Anthropic Skill cannot — **provenance-bound execution.** Regulated buyers (the EU AI Act Article 14 segment) will pay a 5-10x premium for that tier. - -**What we build now (pre-Loop 3):** -- Knowcap MCP is shipped + stable (post-2026-05-19 with `verification_strictness`) -- First-party Vertical Pack: Odoo Partner Pack (with Odoo SH lighthouse demo as anchor) -- Document the Pack format — `pack.json` manifest, file layout, export-to-Anthropic-Skill flow - -**What we do NOT build now:** -- Marketplace UI, payment infrastructure, revenue share, developer portal — all premature before there's organic developer demand. - -**Target:** First-party Odoo Partner Pack live by 2026-07-31. Observe organic third-party MCP usage by year 2. Formalize the Vertical Pack marketplace once 5+ external orgs are shipping packs. - ---- - -## Why three loops on one substrate = a billion-dollar idea - -The three loops share the same data asset AND reinforce each other across time: - -| Year | Spinning loops | Revenue character | -|---|---|---| -| 1 (now) | Loop 1 only | Seat licenses on Odoo partners | -| 2 | Loop 1 + Loop 2 begins | Seats + cross-org "bridge" pricing (charge the second side too) | -| 3 | All three loops | Seats + bridges + marketplace take rate (15–30% on third-party agents) | -| 5 | Loops compound | Seats + bridges + marketplace + COMPLIANCE-CERTIFIED-AGENT marketplace ("only Knowcap-attested agents pass EU AI Act audit") | - -**The compounding moat:** by year 3, leaving Knowcap means losing (a) your historical audit trail, (b) all your cross-org bridges with clients/suppliers, (c) all your installed agents. Each loop adds switching cost the next loop can monetize. - ---- - -## Why nobody else can run all three loops - -| Competitor | Loop 1 ready? | Loop 2 ready? | Loop 3 ready? | -|---|---|---|---| -| Glean | Yes (Enterprise Graph) | **No** — single-tenant by design | Partial (no verification primitive) | -| Read.ai | Yes (meeting capture + MCP) | **No** — single-tenant | Partial (no verification primitive) | -| Mem0 / Zep | Partial (no UX, no buyers) | **No** — infra layer, no two-sided graph | **No** — no marketplace, no end users | -| Salesforce / Notion | Yes | **Partial** — only inside ACL boundary | Yes (AppExchange / etc.) | -| DocuSign | **No** — only documents, not facts | Yes for documents | **No** for AI agents | - -**Knowcap is the only stack where the same substrate supports all three loops.** This is what a billion-dollar moat looks like — not one big advantage, but three smaller advantages that compound on top of each other and would each require a *different competitor* to attack. - ---- - -## Beachhead → vertical expansion sequence - -The flywheel works per-vertical the same way. We start with Odoo partners (where Hassan has insider distribution + a clear lighthouse demo target — meeting → Odoo SH PR) and expand into vertical-adjacent regulated buyers. - -| Order | Vertical | Lighthouse agent action | Why this comes next | -|---|---|---|---| -| 1 | **Odoo partners** | Meeting → Odoo SH PR for client module | Hassan's distribution + SOW-attestation pain + code-shaped work product (easiest agent action) | -| 2 | **Boutique accounting / fractional CFOs** | Meeting → Odoo journal entry / reconciliation memo | Adjacent to Odoo partners; same regulated buyer profile; SMEtools intro path | -| 3 | **Financial advisors** | Meeting → compliance log / client review note | Largest TAM in regulated AI spending; FINRA / MiFID II forced human-attestation | -| 4 | **Legal — boutique / mid-market** | Meeting → matter memo / contract redline triage | ABA Op. 512 + privilege; high $/seat | -| 5 | **Healthcare admin (not clinical)** | Meeting → prior-auth packet / appeal letter | CMS MA Final Rule mandates human review on denials | - -**Do NOT** chase horizontal positioning before Vertical 2 is profitable. Crossing The Chasm — own one tribe, then bridge. - ---- - -## Operational implications for the dev team - -Every feature decision should be evaluated against which loop it accelerates: - -| Question | Loop 1 | Loop 2 | Loop 3 | -|---|---|---|---| -| Does it deepen capture within an existing org? | ✓ | | | -| Does it bring a counterparty (client/supplier/auditor) onto Knowcap? | | ✓ | | -| Does it expose the verified-fact substrate to a third-party developer? | | | ✓ | -| Does it make agents more capable of taking real actions on confirmed facts? | ✓ | | ✓ | - -**Examples in current backlog:** -- ~~Inbox confirm gate fix (the 3 `review_status` ignore-sites)~~ — **DONE 2026-05-12 via PR #305.** Core verification gate is live; memoryService filters + sorts by importance, LLM prompt tags claim/evidence, MCP exposes status filter. -- `confirmation_source` schema split (human-confirmed vs rule-auto-confirmed) — **Loop 1 + Loop 3** (required before rule-promotion UI can ship honestly; see [VERIFICATION-UX.md](./VERIFICATION-UX.md) Mechanism 2) -- Instructions Hierarchy — **Loop 1** (org configurability deepens single-org value) -- Typed edge layer — **Loop 1 + Loop 3** (deepens agent reasoning AND makes the MCP more powerful) -- Cross-org bridges + Parties confirmation surface — **Loop 2** (the network effect mechanism) -- Odoo SH lighthouse demo — **Loop 1 sales proof**; pattern reused in Loop 3 as a reference agent -- MCP `verification_strictness` parameter — **Loop 3** (compliance-gated agent tier) -- "Compliance-attested agent" certification framework — **Loop 3** (regulated-vertical premium) - -**Decision principle:** ship Loop-1 work that proves single-org ROI **before** ship Loop-2 viral mechanics **before** ship Loop-3 marketplace. Do not invert this — a marketplace without proven single-org ROI is empty. - ---- - -## What this strategy is NOT - -- **Not a product roadmap.** Loop sequencing is not a Gantt chart. Specific features ship when their value to the current loop is clear; the strategy doc tells you which loop the feature serves. -- **Not a pitch deck narrative.** External-facing storytelling lives in [POSITIONING.md](./POSITIONING.md). This doc is internal — devs and Hassan use it to align build priorities. -- **Not a substitute for VISION.md.** VISION says *what we are.* STRATEGY says *how the business compounds.* - ---- - -## Companion — product vs. services: who builds what - -The three loops above describe how the **product** compounds. They do not describe the **services** motion that funds the early product and feeds it features. For B2B engagements (implant Knowcap across an org for 30 days → capture → AI strategy → custom automations), the division of labor between **Knowcap (the data plane)** and **Claude/Claw (the build plane)** — and the boundary test for what graduates from a bespoke build into a native Knowcap feature — lives in [`../strategy/knowcap-vs-claude-division-of-labor.md`](../strategy/knowcap-vs-claude-division-of-labor.md). Read it before scoping any custom-automation engagement. diff --git a/docs/brand/VISION.md b/docs/brand/VISION.md deleted file mode 100644 index 0fe3040..0000000 --- a/docs/brand/VISION.md +++ /dev/null @@ -1,330 +0,0 @@ -# Knowcap Vision - -Hassan-owned. Edited when direction changes. The mockup in the `agents-research-complete-ui` worktree (branch `hassan-knowcap-v2`) is the canonical visual spec — this file is the *narrative* that points to it. - -**How devs use this:** read the relevant section before opening a `feat(...)` PR. Link the section from your PR description. Hassan reviews your preview URL against this doc and the mockup frame it points to. - -**Updated:** 2026-05-29 — re-adjudication council ([decision record](./decisions/2026-05-29-mena-council-readjudication.md)): launch re-pegged off the deferred EU AI Act onto Saudi PDPL + GDPR Art 22, MENA stats corrected, lighthouse demo revised, full vision is the plan. Prior 2026-05-25: Adds council research findings: product DNA positioning (Otter + Loom + NotebookLM, verified), market evidence across 15 competitors (Force 4), painkiller analysis by buyer persona, MENA-first go-to-market ruling, platform AI anti-positioning row. Prior update 2026-05-20: Playbooks unification, Instructions Hierarchy, `Party → Person` rename, Anthropic Skills layer. See companion docs [STRATEGY.md](./STRATEGY.md), [POSITIONING.md](./POSITIONING.md), [MOAT.md](./MOAT.md), [VERIFICATION-UX.md](./VERIFICATION-UX.md), [FEATURES-FROM-VISION.md](./FEATURES-FROM-VISION.md), [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md). **2026-06-08:** "The 5 memory categories" reworked into the commitment ontology (Decision · Task · Commitment · Risk · Note) — see [`memory-ontology.html`](./memory-ontology.html); plane-of-labor strategy added at [`../strategy/knowcap-vs-claude-division-of-labor.md`](../strategy/knowcap-vs-claude-division-of-labor.md). - ---- - -## North star - -> **Knowcap turns your meetings into institutional memory your whole team can trust — every fact verified by a named human, every decision traceable to the source.** - -Knowcap is not a meeting notetaker (Read.ai, Otter, Fathom, Granola already own that). Knowcap is not a knowledge-graph platform (Glean already owns that). Knowcap is not AI memory infrastructure (Mem0, Zep, Letta already own that). Knowcap sits **on top of those primitives** and adds the one thing none of them deliver: a record of which facts a named human has confirmed against named evidence — and a contract that AI agents only act on confirmed facts. - -**Product DNA: Otter + Loom + NotebookLM, verified.** Knowcap combines transcription + cross-meeting knowledge (Otter's domain), video recording + sharing (Loom's domain), and multi-source synthesis with timestamped citations (NotebookLM's domain). What none of them deliver: human verification of every extracted fact, cross-org confirmation where both sides attest, and an audit trail that satisfies EU AI Act Article 14. - -Meetings are the highest-density capture channel, but not the only one. Documents, emails, Telegram, WhatsApp, URLs all feed in. The substrate that matters is the verified-fact graph the org accumulates over time, not the input pipe. - -The product experience is: **capture → classify → verify → connect → act.** By the time a meeting ends, every meaningful statement has been extracted, routed to the right project, timestamped to the exact second, and is waiting for one-tap human review. Once confirmed, the statement becomes a verified node in the graph — usable by any human or AI agent with the right scope. - -The AI never acts on unverified information. Every approval is simultaneously a verification and a training signal. - ---- - -## Why this thesis survives even at 100% AI accuracy - -The verification moat is not "we catch hallucinations." It is **provenance + authority + audit trail for any fact an AI agent will act on.** Three forces keep that moat alive regardless of how good the underlying model gets: - -1. **Math.** Multi-step agent workflows compound errors — 20 chained steps at 95% per-step accuracy = 36% end-to-end success. Checkpoints are not optional. -2. **Security.** Prompt injection is "unlikely to ever be fully solved" (OpenAI CISO Dane Stuckey, Dec 2025). An agent reading untrusted content needs a trusted-fact substrate it can fall back on. -3. **Law.** EU AI Act Article 14 (enforcement deferred to Dec 2 2027 via the Digital Omnibus), GDPR Article 22, ESMA's 2024 MiFID II statement, CMS Medicare Advantage 2024 Final Rule, ABA Formal Opinion 512, and the Moffatt v. Air Canada precedent all require human attestation as a non-delegable legal artifact — not because the AI is wrong, but because a *natural person* must be accountable. A 100%-accurate AI still cannot be the legal signatory. -4. **Market evidence.** Research across 15 competitor products (Fireflies, tl;dv, Otter, Sembly, Circleback, Read.ai, Glean, Microsoft Copilot/Work IQ, Mem0, Zep/Graphiti, Letta, Cognee, Google NotebookLM/Workspace Intelligence, Granola) found **zero** with human verification of AI-extracted facts, **zero** with mandatory outgoing approval on agent actions, **zero** with cross-org confirmation, and **zero** with per-fact regulatory audit trails. The gap is unanimous and structural — not a missing feature but a missing architectural primitive. - -Full reasoning + citations in [MOAT.md](./MOAT.md). - ---- - -## Anti-positioning — what Knowcap is NOT - -| Category | Who owns it | Why we don't fight there | -|---|---|---| -| Meeting notetakers | Read.ai, Otter, Fathom, Granola, Fireflies | Commodity. Distribution + feature war. We lose. | -| Enterprise knowledge graph | Glean ($7.2B), Microsoft Graph, Notion AI | Capital + enterprise sales war. We lose. | -| AI memory infrastructure | Mem0, Zep / Graphiti, Letta, Cognee | Developer-mindshare war. We lose. | -| Pure summary accuracy | Every AI lab | Solved by model upgrades. Moat erodes quarter-by-quarter. | -| Platform AI (Google Workspace, Microsoft Copilot) | Google ($2T), Microsoft ($3T) | Platform bundling war. Free at zero marginal cost. We lose on price. | - -Knowcap consumes those primitives and sells the layer **above** them: human-confirmed verified facts that agents can be trusted to act on, with audit trail, in regulated and semi-regulated contexts where a human signature is required. - -Knowcap's product positioning: **Otter + Loom + NotebookLM, verified.** We acknowledge that Otter already claimed 'Conversational Knowledge Engine' (April 28, 2026, BusinessWire). We do not compete on that phrase. Our positioning is 'institutional memory' — adjacent but distinct, encoding the verification layer that Otter's graph lacks. - -Full competitor positioning + buyer profile in [POSITIONING.md](./POSITIONING.md). - ---- - -## Beachhead: Odoo partners → regulated verticals → horizontal - -**Phase 1 (now → +12 months) — Odoo partners.** -Hassan owns SMEtools (an Odoo partner) and has insider distribution to the segment. Odoo partners run client implementation projects where SOW commitments, scope changes, and go-live decisions are litigated in client meetings and lost the moment the meeting ends. The killer feature: **meeting → human-confirmed scope decision → auto-generated Odoo SH PR with attestation trail.** Lighthouse demo target. - -**MENA-first go-to-market (council ruling, May 2026; re-confirmed 2026-05-29).** ~470 Odoo partners across Egypt (~181), Saudi Arabia (~182), UAE (~104) per Odoo's official directory (counts drift — verify before public use). WhatsApp dominates messaging — ~86% of internet users in Saudi Arabia, ~72% in Egypt ([DataReportal 2025](https://datareportal.com/reports/digital-2025-saudi-arabia)) — and phone calls remain heavy; Western tools miss both channels. Arabic ASR is improving but not solved: vendors like Speechmatics advertise *up to* 96% word accuracy with dialect coverage but publish no per-dialect breakdown, and independent 2025 benchmarks (NADI) still show ~38% word-error rates on spontaneous dialect speech — treat Arabic transcription as a buyable input, never a superiority claim. Competition: Arabic-first meeting/STT tools exist (Mudawin, Notah, Munsit, all 2025) — but **none verify facts with a named human**; the literal "0 MENA competitors" claim is false, the true and stronger claim is "0 doing human-verification." Conservative MENA TAM: $100-175M (2025), growing to $300-500M by 2030. Strategy: MENA-first go-to-market, global product. Own the region, expand from revenue, not desperation. - -**Phase 2 (month 6 → year 2) — regulated knowledge work.** -Financial advisors (FINRA Rule 3110, ESMA MiFID II), legal practices (ABA Formal Opinion 512, attorney-client privilege), healthcare (CMS Medicare Advantage Final Rule, HHS OCR Section 1557). These buyers already pay $30–100/user/mo for compliance-grade tools and *want* the verification layer because their regulator mandates it. ~55–65% of enterprise AI spending sits in industries where the human signature is the regulated artifact. - -**Phase 3 (year 2 → year 5) — horizontal expansion via agent marketplace.** -The verified-fact substrate is industry-agnostic. The differentiation per vertical is the *agent action plugin* — Odoo SH PR for partners, contract redline for lawyers, compliance log for advisors. See [STRATEGY.md](./STRATEGY.md) for the three-loop flywheel. - ---- - -## What makes a fact verified - -Verification is two-layered, not one: - -1. **Provenance** — every memory is anchored to a timestamp (recordings), page/paragraph (documents), or message ID (chat). You always know exactly where it came from. Citations are first-class. -2. **Human confirmation** — a named human has promoted the claim to evidence. The graph only contains what a human has confirmed. - -Together these two layers make Knowcap's knowledge trustworthy for AI agents to reason over. Other tools give agents documents or transcripts. Knowcap gives agents facts a human has confirmed are true, with the receipts. - -**Hard rule:** the UX must never allow a bulk "confirm all" action that bypasses individual review. That deletes the moat. See [VERIFICATION-UX.md](./VERIFICATION-UX.md) for what to build instead (bulk-review surface, confidence-thresholded auto-confirm with honest labels, rule promotion, tier-gated agent actions). - ---- - -## The 5 Layer-1 categories (commitment ontology — proposed 2026-06-04) - -Every paragraph of every ingested source is classified into the org's **Layer-1 categories** — the four things an agent acts on, plus one reference type: - -1. **Decisions** — choices made, directions locked -2. **Tasks** — work assigned, actions required, deadlines set -3. **Commitments** *(new)* — a promise the org owes someone: a client, partner, or supplier externally, or manager↔employee internally. Typed fields: `promisor` / `promisee` / `due` / `deliverable` / `source_ref`. A commitment is the SOW baseline; scope creep is a request with no matching commitment behind it. Closes via a `fulfilled_by` or `breached_at` edge. -4. **Risks** — threats, delays, blockers, objections; every risk threatens a commitment -5. **Notes** — the verified substrate the other four stand on (everything that was `fact` + `general`). Agents READ notes as grounding; they never act on a note. - -**Why this membership (4→5 — the number stays ~5, the membership changes).** The org model is a **web of commitments** (see [POSITIONING.md](./POSITIONING.md)): commitments carry risk, risk is mitigated by decisions and tasks, tasks fulfil commitments, notes are the facts it all stands on. So `fact` + `general` collapse into **Note**, and **Commitment** is promoted to a first-class actionable category. **Person / Topic / Speaker leave the category list** — they were never peers of an action; they are **Layer-2 dimensions** every memory is tagged with. `status` stops being a typed box and becomes *derived* from closing edges (`fulfilled_by`, `mitigated_by`, `superseded_by`). - -**Status: proposed, not shipped.** Today's schema still ships `task / risk / decision / fact / general / people`. The migration (`fact`+`general` → `note`, add `commitment` + its edge, demote Person/Topic/Speaker to Layer-2, derive `status` from edges) is specced in [`memory-ontology.html`](./memory-ontology.html) and the main-repo schema ADR. **Sales describes the CURRENT extraction until the migration ships.** - -**These labels are org-configurable via the Instructions Hierarchy.** A sales org defines Risks as sales objections. An ERP team defines Risks as integration failures. A law firm defines Risks as adverse precedent. The categories are the taxonomy; the Instructions Hierarchy defines what they mean for each org. - -**Honest note:** the category labels themselves are not a moat — Read.ai, Otter, and Fellow all extract similar artifacts. The differentiation is (1) **Commitment as a first-class entity** with a promisor/promisee/due structure nobody else models, (2) categories org-tunable through the Instructions Hierarchy, and (3) downstream flow only after human verification. - ---- - -## The living graph — memories connect across meetings - -The graph is the data shape. The verification is the trigger. The agent action is the product. - -Memories don't die when a meeting ends. They evolve: - -- A Risk flagged in meeting 1 → stays open → gets mitigated in meeting 4 → `mitigated_by` edge connects them -- A Decision made in meeting 2 → revisited in meeting 6 → `superseded_by` connects old to new -- A Task assigned in week 1 → completed in a standup 2 weeks later → `completed_by` closes the loop -- A Person builds a sentiment arc across 20 meetings — not a snapshot opinion, a traceable history - -The AI suggests typed edges between memories using semantic similarity + category + Person matching. A human confirms each edge with one tap. Every edge in the graph is verified. No unverified connections pollute the reasoning substrate. - -**Typed edge vocabulary:** -`supports` · `contradicts` · `depends_on` · `derived_from` · `superseded_by` · `mitigated_by` · `completed_by` · `reassigned_to` · `part_of` · `preceded_by` · `followed_by` - -**Honest note (status as of 2026-05-19):** the typed-edge layer is not yet shipped. Target: Sprint 3 (post-2026-05-26). Until then, "queries across meetings" run via RAG over verified-only memories, not via edge traversal. Sales positioning must reflect what's shipped vs what's aspirational — see [POSITIONING.md](./POSITIONING.md) for the "shipped today / aspirational tomorrow" matrix. - ---- - -## The trust ladder — how humans control agent autonomy - -### Per-memory escalation (L1 / L2 / L3) - -When a memory is verified, the user can escalate the response: - -- **L1** — notify the right person before the meeting ends -- **L2** — spin up a research agent: finds how others handled similar situations, returns a formatted report (PDF, email, Telegram post, Slack) for human approval before delivery -- **L3** — research + execute: contacts suppliers, drafts PRDs, opens GitHub branches and PRs, builds mini-applications — all before human approval, then waits for the merge/send signal - -### Per-agent autonomy (T0 / T1 / T2) - -Agent routines earn autonomy through track record: - -- **T0** — every output requires explicit approval before anything happens -- **T1** — auto-approved; human can override within a window -- **T2** — fully autonomous; pings only - -Agents graduate T0 → T1 → T2 based on approved run count, weighted by output impact. A digest agent graduates at 20 approved runs. A code-autopilot graduates at 50+. Trust is earned, not granted. - -Default for all new orgs: **T0 across the board.** The AI never acts beyond what the org has explicitly authorized. - -### Verification strictness scales with action blast radius - -A draft-internal-note agent may run on auto-confirmed facts. An open-Odoo-SH-PR agent or a send-WhatsApp-to-client agent must run only on human-confirmed facts with secondary review. The MCP query layer enforces this per agent tier. See [VERIFICATION-UX.md](./VERIFICATION-UX.md). - ---- - -## The Rules layer — deterministic guardrails - -Four rule families, each with confidence thresholds and AI-suggested promotions: - -- **Routing** — where incoming sources land (`speaker is Khaled AND mentions "PO" → Ariika Default +50`) -- **Extraction** — how the classifier scores statements per org/project/speaker -- **Claim → Evidence** — auto-promote and auto-reject conditions with rollback windows -- **Noise** — what gets dropped before extraction reaches the inbox - -Every human approval pattern that repeats gets suggested back as a rule: *"you've confirmed this 12× — promote to +40?"* The rules layer is the human-readable output of what the AI has learned from approvals. **Crucially:** rule-promoted auto-confirms are stored with a different `source` label than human confirms (`auto_confirmed_rule_v1` vs `human_confirmed`) so the audit trail remains honest and queryable. - ---- - -## The Instructions Hierarchy — 4-tier file-based composition - -Every Knowcap agent run composes its system prompt from four markdown layers, in this order from most general to most specific: - -``` -[ organization.md ] ← org-level identity, vocabulary, tone, category semantics - ↓ -[ projects/{slug}.md ] ← project-specific glossary, scope, special persons / clients - ↓ -[ users/{slug}.md ] ← who's running this — role, escalation defaults, style - ↓ -[ agents/{slug}.md ] ← the Playbook itself — procedure + tools + tier + trigger - ↓ -[ verified facts from MCP ] ← runtime data layer — search_memories(verification_strictness=...) - ↓ - AGENT EXECUTES - ↓ -[ run log with provenance ] ← every verified-fact ID consumed is logged -``` - -Each layer can refine — never silently overwrite — the layer above. A later layer can add or constrain; conflicts surface in the run log so an auditor can reconstruct what the agent saw. - -**Files are canonical, Postgres is a metadata cache.** All four files live in object storage (per-org-scoped). Postgres caches parsed frontmatter for fast UI queries. Optional git-mirror per org allows power users to `git push` edits. Every `agents/{slug}.md` is **Anthropic-Skill-compatible** — it can be exported as a standalone `SKILL.md` for use in Claude Desktop / Cursor / Goose, with the Knowcap-extra frontmatter fields ignored by stock runtimes. - -Full spec: [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md). - -This is what enables a sales org to say "Risks = sales objections, not integration blockers" at the org layer and have every agent in every project in that org classify accordingly — without anyone having to edit every Playbook. - ---- - -## The API — agents query verified knowledge - -Every org gets an API key scoped to that org. External AI agents query the graph via the Knowcap MCP: - -- `search_memories(query, verification_strictness='human_only' | 'rule_auto_ok' | 'all')` — returns facts at the strictness level the calling agent's tier requires -- `get_decisions(project, date_range)` — decision tree for a project -- `get_parties(name)` — sentiment arc + open items for a customer or supplier -- `get_open_risks(project)` — Risk nodes with no `mitigated_by` edge - -The MCP enforces the org boundary. No agent sees outside its API key scope. Project-level scoping is an optional query parameter. **Verification strictness is a required parameter** — an agent cannot accidentally read auto-confirmed claims if it was configured for human-only. - ---- - -## The surfaces - -| Surface | What it does | -|---|---| -| **Inbox** | 5-tab command center: Routing → Agent actions → Claims → Evidence today → Noise | -| **MockPlayer** | Claim-by-claim review within a recording — navigate memory by memory | -| **InboxPreview** | Single-meeting sectioned review: 5 categories + cross-source bridges (SUPPORTS / CONTRADICTS) | -| **Atlas** | Visual knowledge graph — org = galaxy/book, project = star/page, memories = nodes, edges = typed connections | -| **Claims** | Cross-org, cross-project list of all memories: Evidence · Pending · Superseded · Auto-rejected | -| **Agents** | Definition library + Routine bindings (scope × schedule × tier) + Run history → trust ladder | -| **Rules** | Routing / Extraction / Claim-Evidence / Noise rule families with threshold sliders | -| **Sources** | All ingested sources with dedup detection, broadcast ingest, re-extract actions | -| **Projects** | Directory grouped by org with trust tier, pending count, agent draft count | -| **Home** | TrustStrip (6 org health stats) + Timeline + Network + Tiles views | -| **Share page** | Public meeting recap — opt-in thread view traces the full arc across meetings | - ---- - -## Persons — the embedded CRM substrate - -Every Person extracted from meetings builds a profile automatically: -- Role, org, lane, sentiment arc -- Every meeting they appeared in with timestamps -- Open items assigned to or involving them -- Cross-source bridges: what they said that SUPPORTS or CONTRADICTS prior statements -- **Cross-org confirmation surface** — when a Person is also a Knowcap user, they can confirm a shared memory from their side, creating a two-sided verified fact (e.g. Odoo partner + their client both confirm the SOW scope change) - -Knowcap does not replace Salesforce or HubSpot. The graph is the *verified-context substrate*; existing CRM tools receive write-backs from Knowcap agents acting on verified facts. - ---- - -## Painkiller vs vitamin — where Knowcap is urgent - -Research across 5 buyer personas (May 2026 council): - -| Persona | Verdict | The pain | -|---|---|---| -| **Agencies/consultancies** | **Painkiller** | 52% of projects hit scope creep. Agencies lose $1-5K/month. Cross-org confirmation = the feature nobody else has | -| **Multi-company founders/CEOs** | **Painkiller** | 70% of decisions forgotten in 24h. Cross-company contradictions are existential. Knowcap replaces a brain function | -| **Regulated verticals (finance/legal/health)** | **Painkiller** | $63M SEC fines Jan 2025. Saudi PDPL enforcing (since Sep 2024). GDPR Art 22 in force. EU AI Act Art 14 deferred to Dec 2027. Existing compliance budgets | -| **Odoo partners** | **Vitamin → painkiller if repositioned** | The tool is a vitamin; the problem is a painkiller. Sell scope-creep insurance + billable-hour recovery, not meeting intelligence | -| **Sales teams** | **Vitamin — do not target** | Gong owns this ($7B+). Verification is friction for sales reps. Red ocean | - -**Go-to-market sequence:** Agencies/consultancies (highest pain, cross-org is unique) → Multi-company founders (Hassan is the case study) → Regulated verticals (Phase 2, longer sales cycles). Odoo partners are the distribution CHANNEL, not the primary pain persona. - ---- - -## Pre-launch focus (now → 2026-05-31) - -### 1. Inbox confirm gate — SHIPPED (closed 2026-05-12 via PR #305) -Closes the trust ladder UX — a project cannot absorb unreviewed claims. **Status: shipped end-to-end** as of 2026-05-12 (PR #305). The `memoryService` chat-context loader filters `review_status` and sorts by `importance DESC` (confirm = +1.0 boost). The LLM prompt tags every memory with claim/evidence via `tagFor()`. The Knowcap MCP `search_memories` tool accepts a `status` array filter defaulting to `pending+confirmed+edited`. RAG transcript-chunk retrieval is intentionally unaffected (it operates on source chunks, not memories — see `project_knowcap_evidence_gap_in_prod`). - -**Remaining trust-layer work (forward-looking, not a "close-the-gap" task):** -- Add `confirmation_source` column distinguishing `human_confirmed` from `auto_confirmed_rule_v1` (see [VERIFICATION-UX.md](./VERIFICATION-UX.md) Mechanism 2). Schema migration + server + UI. Multi-PR. -- ~~Add `verification_strictness` convenience parameter to MCP~~ **DONE 2026-05-19 via knowcap-mcp PR #7.** Agents call `search_memories(verification_strictness='human_only')` and the MCP enforces the trust tier server-side. - -### 2. Instructions Hierarchy + Playbooks (`hassan-instructions-hierarchy`) -4-tier file-based system prompt composer (`organization.md` → `projects/{slug}.md` → `users/{slug}.md` → `agents/{slug}.md` → verified facts from MCP). Markdown files canonical, Postgres metadata cache. Anthropic-Skill-compatible at the agent layer. See [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md). **Target: 2026-05-23.** - -### 2b. Agents marketplace (renamed Type 1 → Vertical Packs) -Knowcap ships **Vertical Packs** — bundles of `organization.md.template` + `projects/.template` + `users/.template` + 5-10 ready-made `agents/*.md` Playbooks per vertical (Odoo partners, financial advisors, legal practices, healthcare admin). Each pack is also exportable to standalone Anthropic Skill folders for use outside Knowcap. See [STRATEGY.md](./STRATEGY.md) Loop 3. - -### 3. Typed edge layer (post-instructions) -Connect memories across meetings with the 11-edge vocabulary. AI suggests edges on ingest; human confirms. **Target: Sprint 3 (post-2026-05-26).** - -### 4. Reliability hardening (Shady, ongoing) -Every recording transcribes. Every recap generates. Every share page loads. No silent failures. Error monitoring, retry budgets, alerting on production failures. - -### 5. The Odoo SH lighthouse demo -A single end-to-end recorded flow. **Revised 2026-05-29** (see [decision record](./decisions/2026-05-29-mena-council-readjudication.md)): the auto-generated Odoo SH **PR** version is killed (≈0% built, contradicted by the product's own code). The shippable, on-thesis demo is **meeting → human-confirmed memory → Odoo task** (≈75-80% built today). This is the demo every Odoo-partner sales conversation should open with. **Target: pick the date on demo readiness, not a regulatory deadline (EU AI Act Art 14 deferred to Dec 2027).** - ---- - -## Post-launch direction (Q3 2026 onward) - -These are NOT in scope before 2026-05-31. All of them are **agent-action surfaces sitting on top of the verified-fact substrate**, not separate products. - -### VoIP / phone-call ingestion -Phone calls are the second-biggest information channel — especially in markets where everything isn't on Google Meet. VoIP integration brings unstructured phone conversations into the same extraction pipeline as meetings. - -### Mobile app -React Native + Expo. iOS + Android. Read-only view first (meetings, recaps, open items, verification queue). Phase 2: capture on phone, push to Knowcap. - -### Agents marketplace -Orgs install or build agents that act on their verified graph. Triggered by claim confirmation, by time, or by event. Third parties build vertical-specific agents (Odoo SH PR generator, contract redline, compliance log, ecommerce ops) on top of the Knowcap MCP. Revenue share. **This is the year-2-3 flywheel — see [STRATEGY.md](./STRATEGY.md) loop 3.** - -### Cross-org bridges -Founders who run multiple orgs can create explicit read-only bridges between org graphs. A Risk in Ariika linked to a Decision in SMEtools — visible only to people with access to both. Default: hard wall. **The cross-org confirmation network is the year-2 flywheel — see [STRATEGY.md](./STRATEGY.md) loop 2.** - -### Knowcap absorbs daily ops -Email, tasks, bookmarks, morning brief — currently external tools. Post-launch 4-week sprint to make these native Knowcap modules. The graph becomes the user's daily home, not just a meeting layer. - ---- - -## Locked design rules - -1. **Vocabulary lock (updated 2026-05-20).** Pending = "claim". Confirmed = "evidence". Internal id `'people'` displays as **"Person" / "Persons"** (renamed from "Party/Parties" 2026-05-20 — buyer-natural language; "Party" sounded like an event). Speakers ⊂ Persons. Topics are crosscut tags, never a peer category. **Vocabulary updated 2026-05-29: "Playbooks" is RETIRED.** The umbrella only existed to fuse Skills + routing Rules; that fusion is dropped. Canonical = **Skill** (the WHAT — a procedure, `deterministic` or `llm` mode) · **Routine** (the WHEN — trigger + scope + the Skill it fires) · **Run** (a tracked execution) · **Rules** (the deterministic filing/routing layer) · **Connectors** (MCP). "Agent" = the runtime (a Project; + an org-scope inbox agent), not a page. See [`decisions/2026-05-29-agent-skills-routines-architecture.md`](./decisions/2026-05-29-agent-skills-routines-architecture.md), [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md), and [FEATURES-FROM-VISION.md](./FEATURES-FROM-VISION.md). -2. **Palette + font lock.** Background `#FBFAF8`. Borders `#E7E4DD`. Ink `#18181B`. Org colors: Knowcap `#1F6B3A`, Ariika `#4A2FA8`, SMEtools `#B5731A`. Titles in `Space_Grotesk`, mono in `JetBrains_Mono`. -3. **No shortcuts.** No fake pickers, no unwired chips, no hardcoded lists, no claiming UI works without `npx tsc --noEmit` clean + a real screenshot. -4. **Mockup-data only in `agents-research-complete-ui` worktree.** The mockup IS the spec — wiring happens on `hassan` / `shady` branches. -5. **Every `feat(...)` PR links a section of this document.** If the feature isn't in this doc, the PR is closed and work goes back to Hassan to update the vision first. -6. **No "Confirm All" button.** Ever. See [VERIFICATION-UX.md](./VERIFICATION-UX.md) for what to build instead when employees complain about per-memory review time. -7. **Anthropic Skills compatibility (locked 2026-05-20).** Every `agents/{slug}.md` Playbook is a strict superset of the Anthropic SKILL.md format. Knowcap is NOT competing with Anthropic Skills — we layer the Instructions Hierarchy, verified facts, and audit trail above their format. Exports trivially to standalone Skill folders for any Skills-aware runtime. - -Full design system: `~/Github/knowledge/llm-wiki/wiki/Knowcap/knowcap-mockup-design-system.md` - ---- - -## What lives outside this doc - -- **Three-loop flywheel + sequencing:** [STRATEGY.md](./STRATEGY.md) -- **Anti-positioning + buyer profile + competition:** [POSITIONING.md](./POSITIONING.md) -- **Why verification survives at 100% AI accuracy:** [MOAT.md](./MOAT.md) -- **How verification UX should and should not work:** [VERIFICATION-UX.md](./VERIFICATION-UX.md) -- **4-tier Instructions Hierarchy spec (org/project/user/agent):** [INSTRUCTIONS-HIERARCHY.md](./INSTRUCTIONS-HIERARCHY.md) -- **Playbooks UX + product behaviors derived from the vision:** [FEATURES-FROM-VISION.md](./FEATURES-FROM-VISION.md) -- **Inbox-zero contract that enforces the verification thesis:** [INBOX-FIRST.md](./INBOX-FIRST.md) -- **Tactical bug list:** Odoo project 141 (customer-reported bugs only) -- **Code ownership:** [OWNERSHIP.md](./OWNERSHIP.md) -- **Approval rules:** [APPROVALS.md](./APPROVALS.md) -- **Lane snapshot:** `.claude/rules/team-operating-model.md` diff --git a/docs/brand/decisions/2026-05-25-strategic-council.md b/docs/brand/decisions/2026-05-25-strategic-council.md deleted file mode 100644 index 63606be..0000000 --- a/docs/brand/decisions/2026-05-25-strategic-council.md +++ /dev/null @@ -1,103 +0,0 @@ ---- -title: "Strategic Council — Vision Thesis Stress Test" -type: decision -company: Knowcap -date: 2026-05-25 -status: superseded -source: "Claude Code session — 20 agents deployed across 3 waves" ---- - -# Strategic Council — Vision Thesis Stress Test (May 25, 2026) - -> **⚠️ SUPERSEDED / CORRECTED 2026-05-29.** This council read the stale `main` branch and assumed slow build velocity. Its "kill list," velocity-driven GTM, and EU-AI-Act launch peg are re-adjudicated in [2026-05-29-mena-council-readjudication.md](./2026-05-29-mena-council-readjudication.md). The MENA-first ruling stands; the stats below (Speechmatics "96% on dialects," "WhatsApp 77%," Odoo "187/181/105," "Zero competitors") are corrected there. Read the correction alongside this. - -## What happened - -Hassan's thesis ("Knowcap is the trust layer for AI agents") was challenged by another Claude agent who argued: "If you just approve the outgoing email, you get 80% of the same protection without verifying each incoming claim." Hassan was shaken and commissioned a full strategic council. - -## The council - -- **20 agents total** across 3 waves -- **Wave 1:** 6 meeting notetaker competitors (Fireflies, tl;dv, Otter, Sembly, Circleback, Read.ai) + MENA market analysis -- **Wave 2:** 4 knowledge-layer competitors (Glean, Microsoft Copilot/Work IQ, AI memory infra (Mem0/Zep/Letta/Cognee), Google NotebookLM/Granola) -- **3 judges:** Moat Skeptic, Go-to-Market Realist, Thesis Synthesizer -- **5 painkiller/vitamin persona tests:** Odoo partners, regulated verticals, multi-company founders, sales teams, agencies/consultancies - -## Key findings - -### Competitive landscape (15 products, 4 layers) -- **0/15 have human verification** of AI-extracted facts -- **0/15 have mandatory outgoing approval** on agent actions -- **0/15 have cross-org confirmation** -- **0/15 have per-fact regulatory audit trails** -- Otter claimed "Conversational Knowledge Engine" on April 28, 2026 — that positioning is taken -- Glean downgraded from existential threat to narrative competitor (different product, buyer, price point) -- Mem0 production audit (GitHub #4573): **97.8% of AI-extracted memories were junk** without human review - -### MENA market -- 470+ Odoo partners across Egypt (187), Saudi (181), UAE (105) -- Zero competitors have MENA offices, local pricing, RTL, or Odoo integration -- WhatsApp 77% adoption in Saudi, phone calls dominant — Western tools miss both -- Arabic ASR improving (Speechmatics 96% on dialects) -- Regulation accelerating: Saudi PDPL (enforcing), UAE PDPL (active), Egypt Decree 816/2025 -- TAM: $100-175M (2025), growing to $300-500M by 2030 - -### Painkiller vs vitamin -| Persona | Verdict | -|---|---| -| Agencies/consultancies | **Painkiller** — scope creep = $1-5K/month, cross-org confirmation is unique | -| Multi-company founders | **Painkiller** — replaces a brain function, 70% of decisions forgotten in 24h | -| Regulated verticals | **Painkiller** — $63M SEC fines, EU AI Act Aug 2026, Saudi PDPL enforcing | -| Odoo partners | **Vitamin → painkiller if repositioned** — sell scope-creep insurance, not meeting notes | -| Sales teams | **Vitamin — do NOT target** — Gong owns this ($7B+) | - -## Decisions made - -### 1. North star changed -**Before:** "Knowcap is the trust layer for AI agents — every fact they act on is confirmed by a named human, with a full audit trail." -**After:** "Knowcap turns your meetings into institutional memory your whole team can trust — every fact verified by a named human, every decision traceable to the source." - -### 2. Product DNA defined -**Knowcap = Otter + Loom + NotebookLM, verified.** Combines transcription + cross-meeting knowledge (Otter), video recording + sharing (Loom), multi-source synthesis with citations (NotebookLM). Plus: human verification, cross-org confirmation, audit trail. - -### 3. MENA-first go-to-market -Go MENA-first, global product. Own the region in 18 months, expand from revenue, not desperation. Careem playbook (global product, MENA distribution). - -### 4. Sidebar layout locked -Groups map to the brand: Know(ledge) + Cap(ture) → **Capture → Knowledge → Act** - -``` -Home -CAPTURE: Inbox, Sources, Voiceprints, Ask Knowcap -KNOWLEDGE: Projects, Claims, Atlas -ACT: Skills, Integrations -Utility: Instructions, Developers, Settings -``` - -### 5. Agents renamed to Skills -Sidebar item, page name, routes — all "Skills." Internally, each Skill has mode: deterministic (rules) or llm (agent procedures). - -### 6. Verification thesis survived — repositioned -Verification is the foundation, not the headline. The moat is the confirmed institutional memory graph — compounding, human-attested, cross-meeting knowledge that gets more valuable every month. Verification is the quality-control mechanism that keeps the graph trustworthy. - -### 7. Glean downgraded -From "existential threat" to "narrative competitor." Different product ($80K+/yr), different buyer (Fortune 2000 CIOs), no meeting-first capture, no Arabic/MENA, no cross-org. - -### 8. Sales teams excluded -Do NOT target. Gong owns this ($7B+, $250/user). Verification is friction for sales reps. Red ocean. - -### 9. Go-to-market sequence -Agencies/consultancies (highest pain) → Multi-company founders (Hassan = case study) → Regulated verticals (Phase 2). Odoo partners are the distribution CHANNEL, not the primary pain persona. - -## 90-day action plan (Judge 3 ruling) -1. **Weeks 1-6:** Ship Odoo integration + close 3 paying Odoo partners -2. **Weeks 3-8:** Build the "confirmed memory" 90-second demo video -3. **Weeks 6-12:** File Saudi PDPL + UAE PDPL compliance positioning - -## Artifacts produced -- PR #694: VISION.md + MOAT.md + UI-PLACEMENT-GUIDE.md updates + full docs audit -- This decision file -- Developer prompt for Skills sidebar implementation (self-contained /goal prompt) - -## The one number -Mem0's production audit: **97.8% of AI-extracted memories were junk without human review.** Use in every sales conversation. diff --git a/docs/brand/decisions/2026-05-29-mena-council-readjudication.md b/docs/brand/decisions/2026-05-29-mena-council-readjudication.md deleted file mode 100644 index a4e402f..0000000 --- a/docs/brand/decisions/2026-05-29-mena-council-readjudication.md +++ /dev/null @@ -1,128 +0,0 @@ -# Re-Adjudication Council — Strategic Correction - -**Date:** 2026-05-29 -**Supersedes:** [`decisions/2026-05-25-strategic-council.md`](./2026-05-25-strategic-council.md) (corrects, does not delete) -**Status:** Locked by Hassan, 2026-05-29 - -## Context - -The 2026-05-25 strategic council ran on two false premises: - -1. **It read the stale `main` branch.** The real work is on the `hassan` branch: **+33,760 / −6,286 lines, 176 files, 391 commits, May 18–29**. The council reasoned about a codebase that no longer reflects reality. -2. **It assumed human-team build velocity.** Premise: features take quarters. Reality: the remaining vision is a ~3-week build. - -Both premises are wrong, so the 2026-05-25 conclusions that depended on them (the "kill list", the velocity-driven GTM, the launch-timing peg) are re-adjudicated here. - -**Team shape for the math below:** Hassan does not code. Shady builds everything — including `knowcap-mcp` — from June 2026 onward. Hassan writes detailed PR specs. Velocity figures are Shady-with-Claude figures, not a team-of-engineers estimate. - -## The Decision (rulings) - -### 1. Market: MENA-first, Egypt beachhead, then US - -Unanimous **3/3 across both councils.** Build speed fixes the **product**, not the **go-to-market**. The US is blocked by factors no amount of faster code can move: - -- ~**$1,461 fintech CAC** -- **SOC2 Type 2** — 6–12 month *calendar* clock (observation window, not a build) -- **6–18 month** regulated-industry sales cycles -- **$281M** competitor funding - -None of these are fixable by shipping code faster. MENA-first stands. - -### 2. Build the full vision — don't strip it - -Honest velocity is **~2,000 logic-lines/day** — **NOT 10k**. The 10k figure was one burst plus a UI-port commit, not a sustainable rate. At ~2,000 logic-lines/day, the **full remaining vision is ~3 weeks of build.** - -Therefore the 2026-05-25 **kill list is REVERSED.** The items it proposed cutting — - -- Skills runtime -- the `confirmation_source` / cross-org / typed-graph moat -- "dead" Odoo code - -— are either **already built** or a **2–3 week build**, not the 12–18 month build the prior council assumed. Nothing on the kill list gets cut. - -### 3. Honesty gap is the #1 priority fix — and it INVERTS the prior advice - -The 2026-05-25 council said: water down the copy to match what the code does. **Reversed.** Build the code to make the claim TRUE instead: - -> "agents act only on human-verified facts" - -This is a **2–4 day `confirmation_source` build**, not a copy edit. Do **not** weaken the positioning. Spec: [honesty-fix-confirmation-source.md](https://github.com/Knowcap-V2/knowcap/blob/main/docs/proposals/honesty-fix-confirmation-source.md). - -### 4. New bottleneck = founder SELLING hours + calendar-bound items — not building - -With building no longer the constraint, the critical path is: - -- founder **selling** hours -- the **SOC2** calendar clock -- the **Odoo lighthouse design-partner sign-off** — **overdue since May 26** -- **3 paying pilots** -- **demand signal** - -Building is not on the critical path. Founder time and calendar-bound external clocks are. - -### 5. Re-peg launch timing — off the (now-deferred) regulatory deadline - -**EU AI Act Article 14 was deferred** from **Aug 2 2026 → Dec 2 2027** (Digital Omnibus, announced ~May 7 2026). The old "why now" hard deadline is gone. - -Re-anchor the "why now" to instruments that are actually in force: - -- **Saudi PDPL** — enforced since **Sep 2024** -- **GDPR Article 22 / CJEU SCHUFA** - -**Pick the launch date on Odoo-demo readiness, not on a regulatory deadline.** - -### 6. Lighthouse demo — kill the unbuildable version, ship the buildable one - -- **KILLED:** the "meeting → auto-generated Odoo SH PR" demo. It is **~0% built** and is **contradicted by the product's own code** — we'd be demoing something the codebase doesn't do. -- **REPLACES IT:** "meeting → human-confirmed memory → Odoo task." This is **~75–80% built** and is on-thesis (it routes through human confirmation, which is the whole point of the product). - -### 7. Stats to correct everywhere - -The docs currently assert these. They are wrong — fix on contact (verified via live sources 2026-05-29): - -| Claim in docs | Reality | -|---|---| -| "Speechmatics 96% on dialects" | **Misleading** — 96% is an *up to* / peak MSA number; no per-dialect breakdown is published. Independent 2025 NADI benchmarks show ~38% WER on spontaneous dialect speech. | -| "WhatsApp 77% Saudi" | **Understated** — ~86% of internet users in Saudi; ~72% in Egypt (DataReportal 2025). | -| Odoo partner split "187/181/105" | **Off** — Odoo's directory shows ~181 Egypt / ~182 Saudi / ~104 UAE (~470 total); counts drift, verify before public use. | -| "0 MENA competitors" | **False for notetakers** — Mudawin, Notah, Munsit exist. **True only for verified-memory** ("0 doing human-verification"). | - -## Why (corrected assumptions + evidence) - -| Prior assumption (2026-05-25) | Corrected assumption (2026-05-29) | Evidence | -|---|---|---| -| The codebase is what's on `main` | The real work is on `hassan` | **+33,760 / −6,286, 176 files, 391 commits, May 18–29** | -| Build velocity is human-team (features = quarters) | ~2,000 logic-lines/day; full vision ≈ 3 weeks | 10k was one burst + a UI-port commit, not a rate | -| Moat/Skills/Odoo code is a 12–18mo build → cut it | Already built or a 2–3 week build → keep it | corrected velocity applied to the actual `hassan` diff | -| Copy over-claims → soften the copy | Code under-delivers → build the code, keep the copy | `confirmation_source` is a 2–4 day build | -| Building is the bottleneck → optimize for build speed | Founder selling + calendar clocks are the bottleneck | SOC2 6–12mo, Odoo sign-off overdue since May 26, pilots/demand still open | -| Launch is pegged to EU AI Act Art. 14 (Aug 2 2026) | Art. 14 deferred to Dec 2 2027; peg to PDPL + GDPR Art. 22 instead | Digital Omnibus, announced ~May 7 2026; PDPL enforced Sep 2024 | -| Lighthouse = meeting → auto-generated Odoo SH PR | meeting → human-confirmed memory → Odoo task | SH-PR demo ~0% built and contradicted by product code; replacement ~75–80% built | - -## What changed from the 2026-05-25 council - -| 2026-05-25 ruling | 2026-05-29 ruling | Direction | -|---|---|---| -| Strip the vision; ship a kill list | Build the full vision; kill list REVERSED | Reversed | -| Soften the honesty copy to match code | Build the code to make the copy true | Reversed | -| Build speed is the lever; optimize for it | Build is no longer the bottleneck; founder selling + calendar are | Reversed | -| Peg launch to EU AI Act Art. 14 (Aug 2 2026) | Art. 14 deferred to Dec 2 2027; peg to PDPL + GDPR Art. 22; launch on demo-readiness | Re-pegged | -| Lighthouse = meeting → Odoo SH PR | Lighthouse = meeting → human-confirmed memory → Odoo task | Replaced | -| MENA-first, Egypt → US | MENA-first, Egypt → US | **Unchanged (3/3 both councils)** | - -## Locked calls (Hassan, 2026-05-29) - -1. `confirmation_source` legacy bulk rows = **`'human'`**. -2. Fix `buildProjectContext` `system_seed` handling **now**. -3. **Shady owns all coding**, including `knowcap-mcp`. - -## Docs synced with this record (2026-05-29) - -- [x] [`VISION.md`](../VISION.md) — date re-pegged, MENA stats corrected, lighthouse demo revised, header updated -- [x] [`MOAT.md`](../MOAT.md) — Art 14 date corrected, window re-pegged to PDPL + GDPR Art 22, lighthouse line revised -- [x] [`POSITIONING.md`](../POSITIONING.md) — stats corrected, compliance-window section re-pegged -- [x] `marketing-content-plan.md` — launch peg, content piece #15, regulatory brief re-pegged; moat-in-content note added -- [x] `june-2026-gtm-game.md` — XP/no-XP contradiction in anti-cheat removed -- [x] [`decisions/2026-05-25-strategic-council.md`](./2026-05-25-strategic-council.md) — superseded-by banner + stat corrections -- [x] [odoo-sh-lighthouse.md](https://github.com/Knowcap-V2/knowcap/blob/main/docs/proposals/odoo-sh-lighthouse.md) — superseded banner (SH-PR demo killed) -- [ ] `STRATEGY.md` — no hard factual error (Art 14 used as a segment label); revisit launch-timing language on next edit diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/index.html b/docs/brand/design-explorations/shotgun-2026-06-10/index.html deleted file mode 100644 index 7c898aa..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/index.html +++ /dev/null @@ -1,74 +0,0 @@ - - - - - -Design Shotgun — Knowcap Commitment Homepage · 2026-06-10 - - - -

Design Shotgun — Knowcap Commitment Homepage 2026-06-10

-

Same locked copy on every variant ("Your company's deepest knowledge is its commitments and the risks against them. Knowcap makes sure they're kept."). Five design languages — different fonts, palettes, and layouts per the anti-convergence rule. Click any card to open the full variant.

- -
-
-

V1 — Impeccable Brass Dossier

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Legal-document craft · Newsreader serif + Georgia · navy ink, cool paper, BRASS accent · centered dossier column, EXHIBIT A framing

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Open V1 full page →
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- -
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V2 — Editorial Light

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Magazine cover, NO dark hero · Fraunces + Inter · cream + green · asymmetric grid, ledger as marginalia column

-
-
Open V2 full page →
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- -
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V3 — Brutalist Registry

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Raw register · Archivo Black + JetBrains Mono · white/black + signal green · 2px borders, the ledger as an actual table, stamps

-
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Open V3 full page →
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- -
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V4 — Kinetic Dark (current PR #34)

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What's on the branch today · Space Grotesk + JetBrains Mono · dark hero, glowing animated ledger, cream body, §-register sections

-
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Open V4 full page →
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- -
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V5 — Product-Led Light

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Linear/Vercel school · Inter + JetBrains Mono · near-white + green · centered hero, CSS-drawn app window as the showpiece

-
-
Open V5 full page →
-
-
- -
- How to pick: open each full page, scroll it, then tell Claude — e.g. "V2 wins" or remix: "V2 layout with V1's brass" / "V5's app window inside V4's dark hero". The winner gets rebuilt as the real Next.js homepage on PR #34 (nothing is pushed until you choose). Old A/B variants are untouched at /a /b /c /d. -
- - diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v1-impeccable-brass.html b/docs/brand/design-explorations/shotgun-2026-06-10/v1-impeccable-brass.html deleted file mode 100644 index e013fd3..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v1-impeccable-brass.html +++ /dev/null @@ -1,972 +0,0 @@ - - - - - -V1 — Impeccable Brass · Knowcap - - - - - -
- -
-
- ✓ - Knowcap · MCP Server for Claude, Codex & Gemini -
-
- -
-

- Your company's deepest knowledge is its commitments and the risks against them.
- Knowcap makes sure they're kept. -

- -

- Your client was promised delivery by June. Your team lead promised the demo would work. - Those promises live in conversations, and they die there. Knowcap captures every commitment - spoken aloud, flags every risk against it, and lets your AI agents act on it — - after a named human confirms it. -

- -
- Most AI agents act on what the AI thinks is true. - Knowcap agents act only on what a human said is true. -
- -
- Get Started Free - Book a Demo -
- -
- Built by an Odoo partner - · - MCP-native - · - Full audit trail on every action -
-
-
- - -
-
-
- Exhibit A — client call, 0:14:32 - Entered into the record -
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0:14:32
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Client
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“We need this live before Ramadan.”

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- Commitment - ⏳ Pending your confirm -
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- -
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0:14:33
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-
Knowcap
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Linked to project Atlas-ERP. Conflicts with the supplier - lead time confirmed last week.

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- Risk - ⏳ Pending -
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- -
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0:14:35
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-
You — one tap
- ✓ Verified -

→ agent drafts the change-order email

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- -

Filed by Knowcap before the meeting ended

-
- - -
-
Article I · What Dies in the Conversation
- -

The deadline slipped because the promise never lived anywhere.

- -

- A company makes hundreds of promises a week. To clients. To employees. To suppliers. - None of them live in your project tool. They live in calls, voice notes, and chat threads. - When one breaks, you find out last. -

- -
-
-
1.1
-
-
The client promise
- “We'll deliver by June.” -

Said on a Zoom call. Never made it into the SOW. The scope grew, - the date didn't move, and the margin paid for it.

-
-
- -
-
1.2
-
-
The internal promise
- “It'll be ready for the demo.” -

Said in standup. Slipped out of standup three weeks ago. - The demo found out for you.

-
-
- -
-
1.3
-
-
The supplier promise
- “Lead time is four weeks.” -

Said on a phone call. Shipped in six. Your customer churned - and your team never saw it coming.

-
-
-
- -

- That is not a project-management problem. It is an open loop. - Knowcap closes it. -

-
- - -
-
Article II · Procedure
- -

Listen. Extract. Confirm. Act.

- -
-
-
I
-
-

Listen

-

Knowcap captures the conversations your team is already having: meetings, - recordings, voice notes, documents, Telegram.

-
-
- -
-
II
-
-

Extract

-

AI pulls out every commitment, decision, task, and risk. Each one carries its - speaker and a timestamp back to the exact second it was said.

-
-
- -
-
III
-
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Confirm

-

A named human reviews each claim and promotes it to evidence with one tap. - No bulk approve. No silent ingestion. The graph holds what your team confirmed, - nothing else.

-
-
- -
-
IV
-
-

Act

-

Agents work from confirmed facts: draft the change-order email, create the - Odoo task, brief the next meeting. Every action carries its receipts.

-
-
-
- -

- Confirmation takes about two minutes per meeting. - The agent actions it unlocks run before the meeting ends. -

-
- - -
-
-
- -

- Organizations aren't hierarchies.
- They're webs of commitments. -

- -

AI is finally able to make sure they're kept.

- -
- Get Started Free - Book a Demo -
-
-
- -
-

Knowcap is verified knowledge for AI agents. Humans confirm. Agents act.

-
- - - - - diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v2-editorial-light.html b/docs/brand/design-explorations/shotgun-2026-06-10/v2-editorial-light.html deleted file mode 100644 index 91d0276..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v2-editorial-light.html +++ /dev/null @@ -1,751 +0,0 @@ - - - - - -V2 — Editorial Light · Knowcap - - - - - - - - -
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- Knowcap · MCP server for Claude, Codex & Gemini - Knowcap - Vol. 01 — Commitments -
-
- - -
-
- -
-

Your company’s deepest knowledge is its commitments and the risks against them. Knowcap makes sure they’re kept.

- -

Your client was promised delivery by June. Your team lead promised the demo would work. Those promises live in conversations, and they die there. Knowcap captures every commitment spoken aloud, flags every risk against it, and lets your AI agents act on it — after a named human confirms it.

- -
- Get Started Free - Book a Demo -
- -
- Built by an Odoo partner·MCP-native·Full audit trail on every action -
-
- - - -
-
- - -
-
- Doctrine -
Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true.
-
-
- - -
-
-
- What dies in the conversation -

The deadline slipped because the promise never lived anywhere.

-

A company makes hundreds of promises a week. To clients. To employees. To suppliers. None of them live in your project tool. They live in calls, voice notes, and chat threads. When one breaks, you find out last.

-
- -
-
- № 1 — The client promise -

“We’ll deliver by June.”

-

Said on a Zoom call. Never made it into the SOW. The scope grew, the date didn’t move, and the margin paid for it.

-
-
- № 2 — The internal promise -

“It’ll be ready for the demo.”

-

Said in standup. Slipped out of standup three weeks ago. The demo found out for you.

-
-
- № 3 — The supplier promise -

“Lead time is four weeks.”

-

Said on a phone call. Shipped in six. Your customer churned and your team never saw it coming.

-
-
- -

That is not a project-management problem. It is an open loop. Knowcap closes it.

-
-
- - -
-
-
- How it works — the loop -

Listen. Extract. Confirm. Act.

-
- -
-
-
01
-

Listen

-

Knowcap captures the conversations your team is already having: meetings, recordings, voice notes, documents, Telegram.

-
-
-
02
-

Extract

-

AI pulls out every commitment, decision, task, and risk. Each one carries its speaker and a timestamp back to the exact second it was said.

-
-
-
03
-

Confirm

-

A named human reviews each claim and promotes it to evidence with one tap. No bulk approve. No silent ingestion. The graph holds what your team confirmed, nothing else.

-
-
-
04
-

Act

-

Agents work from confirmed facts: draft the change-order email, create the Odoo task, brief the next meeting. Every action carries its receipts.

-
-
- -

Confirmation takes about two minutes per meeting. The agent actions it unlocks run before the meeting ends.

-
-
- - -
-
-
-
- Knowcap · The thesis -

Organizations aren’t hierarchies.
They’re webs of commitments.

-

AI is finally able to make sure they’re kept.

-
-
- Get Started Free - Book a Demo -
-
-
-
- - -
-
- Knowcap is verified knowledge for AI agents. Humans confirm. Agents act. - © 2026 Knowcap -
-
- - - - diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v3-brutalist-registry.html b/docs/brand/design-explorations/shotgun-2026-06-10/v3-brutalist-registry.html deleted file mode 100644 index 455423d..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v3-brutalist-registry.html +++ /dev/null @@ -1,682 +0,0 @@ - - - - - -V3 — Brutalist Registry · Knowcap - - - - - - - - - -
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- - -
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- - -
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- REG. NO. 0001 - DOC CLASS: COMMITMENT REGISTER - ISSUED: 2026-06-10 - STATUS: ● LIVE -
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- - -
-
-

Knowcap · MCP server for Claude, Codex & Gemini

- -

- Your company’s deepest knowledge is its commitments and the risks against them. - Knowcap makes sure they’re kept. -

- -

Your client was promised delivery by June. Your team lead promised the demo would work. Those promises live in conversations, and they die there. Knowcap captures every commitment spoken aloud, flags every risk against it, and lets your AI agents act on it — after a named human confirms it.

- -
- Doctrine -

Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true.

-
- -
- Get Started Free - Book a Demo -
- -
    -
  • Capture meetings, recordings, voice notes, documents, URLs, and Telegram
    • -
  • AI extracts every commitment, decision, task, and risk — with the speaker and the timestamp
    • -
- -
- Built by an Odoo partner - MCP-native - Full audit trail on every action -
-
-
- - -
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- EXHIBIT A - LIVE MEETING — ENTRIES AS SPOKEN -
- -
- COMMITMENT REGISTER - REC 0:14:35▌ -
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- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
TimeSpeakerEntryClassStatus
0:14:32ClientWe need this live before Ramadan.Commitment⏳ Pending your confirm
0:14:33KnowcapLinked to project Atlas-ERP. Conflicts with the supplier lead time confirmed last week.Risk⏳ Pending
0:14:35YouOne tap → agent drafts the change-order email.Confirm✓ Verified
-
- -
- ✓ EVERY ENTRY CARRIES ITS SPEAKER, ITS TIMESTAMP, AND THE NAMED HUMAN WHO CONFIRMED IT. -
-
-
- - -
-
-
- SEC. 002 - What dies in the conversation -
- -

The deadline slipped because the promise never lived anywhere.

- -

A company makes hundreds of promises a week. To clients. To employees. To suppliers. None of them live in your project tool. They live in calls, voice notes, and chat threads. When one breaks, you find out last.

- -
-
-

001

-

“We’ll deliver by June.”

-

The client promise

-

Said on a Zoom call. Never made it into the SOW. The scope grew, the date didn’t move, and the margin paid for it.

-
-
-

002

-

“It’ll be ready for the demo.”

-

The internal promise

-

Said in standup. Slipped out of standup three weeks ago. The demo found out for you.

-
-
-

003

-

“Lead time is four weeks.”

-

The supplier promise

-

Said on a phone call. Shipped in six. Your customer churned and your team never saw it coming.

-
-
- -

That is not a project-management problem. It is an open loop. Knowcap closes it.

-
-
- - -
-
-
- SEC. 003 - How it works — the loop -
- -

Listen. Extract. Confirm. Act.

- -
-
-

01

-

Listen

-

Knowcap captures the conversations your team is already having: meetings, recordings, voice notes, documents, Telegram.

-
-
-

02

-

Extract

-

AI pulls out every commitment, decision, task, and risk. Each one carries its speaker and a timestamp back to the exact second it was said.

-
-
-

03

-

Confirm

-

A named human reviews each claim and promotes it to evidence with one tap. No bulk approve. No silent ingestion. The graph holds what your team confirmed, nothing else.

-
-
-

04

-

Act

-

Agents work from confirmed facts: draft the change-order email, create the Odoo task, brief the next meeting. Every action carries its receipts.

-
-
- -

Confirmation takes about two minutes per meeting. The agent actions it unlocks run before the meeting ends.

-
-
- - -
-
-

- Organizations aren’t hierarchies.
- They’re webs of commitments. -

-

AI is finally able to make sure they’re kept.

-
- Get Started Free - Book a Demo -
-
-
- - -
-
-

Knowcap is verified knowledge for AI agents. Humans confirm. Agents act.

-

© 2026 Knowcap · V3 — Brutalist Registry

-
-
- - - diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v4-kinetic-dark.html b/docs/brand/design-explorations/shotgun-2026-06-10/v4-kinetic-dark.html deleted file mode 100644 index 39abf4e..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v4-kinetic-dark.html +++ /dev/null @@ -1,258 +0,0 @@ -Knowcap — The Trust Layer for AI Agents
Knowcap
Get Started Free
Knowcap · MCP server for Claude, Codex & Gemini

Your company’s deepest knowledge is its commitments and the risks against them.Knowcap makes sure they’re kept.

Your client was promised delivery by June. Your team lead promised the demo would work. Those promises live in conversations, and they die there. Knowcap captures every commitment spoken aloud, flags every risk against it, and lets your AI agents act on it — after a named human confirms it.

Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true.

Get Started Free Book a Demo
Built by an Odoo partnerMCP-nativeFull audit trail on every action
Captures Meet · recordings · voice notes · documents · URLs · Telegram

The deadline slipped because the promise never lived anywhere.

A company makes hundreds of promises a week. To clients. To employees. To suppliers. None of them live in your project tool. They live in calls, voice notes, and chat threads. When one breaks, you find out last.

The client promise
“We’ll deliver by June.”

Said on a Zoom call. Never made it into the SOW. The scope grew, the date didn’t move, and the margin paid for it.

The internal promise
“It’ll be ready for the demo.”

Said in standup. Slipped out of standup three weeks ago. The demo found out for you.

The supplier promise
“Lead time is four weeks.”

Said on a phone call. Shipped in six. Your customer churned and your team never saw it coming.

That is not a project-management problem. It is an open loop. Knowcap closes it.

Listen. Extract. Confirm. Act.

01

Listen

Knowcap captures the conversations your team is already having: meetings, recordings, voice notes, documents, Telegram.

02

Extract

AI pulls out every commitment, decision, task, and risk. Each one carries its speaker and a timestamp back to the exact second it was said.

03

Confirm

A named human reviews each claim and promotes it to evidence with one tap. No bulk approve. No silent ingestion. The graph holds what your team confirmed, nothing else.

04

Act

Agents work from confirmed facts: draft the change-order email, create the Odoo task, brief the next meeting. Every action carries its receipts.

Confirmation takes about two minutes per meeting. The agent actions it unlocks run before the meeting ends.

80 seconds

Meeting → confirmed scope change → Odoo task.

Your client says “add the warehouse module to phase two.” Knowcap captures it, timestamps it, classifies it as a scope decision, and puts it in your inbox. You confirm with one tap. Before the meeting ends, the task is in your Odoo project with the client’s exact words attached — and the change-order conversation is already drafted.

Scope creep is a request with no commitment backing it. Knowcap flags the gap while the client is still on the call.

Knowcap inbox: a scope-change claim awaiting one-tap confirmationVERIFIED

RAID logs, action trackers, contract tools — they all died the same way.

They captured the right things: commitments, risks, decisions, tasks. They all collapsed at the same point: a human had to maintain them by hand. The discipline lasted two sprints and then real work won.

You can’t add discipline on top of existing work. You have to remove the friction until the discipline becomes automatic.

Knowcap inverts the old model. The capture is automatic. The judgment stays human: one tap that turns an AI extraction into a fact your agents can rely on. That confirm-then-act loop is not a UX detail. It is the product.

52%

of agency projects hit scope creep

70%

of meeting decisions are forgotten within 24 hours

15 → 0

competitor products examined. Zero verify facts with a named human.

Your agents, your tools, your verified facts.

Knowcap ships as an MCP server. Connect it to Claude, Codex, or Gemini and your agents query your organization’s confirmed knowledge instead of guessing from transcripts. Ask what was promised to a client, what risks are open against the launch, what changed since last week. The answers come with receipts: who said it, when, and who confirmed it.

Works inside the AI tools you already useAgents read confirmed facts only — strictness is enforced server-side, per agentEvery fact links back to the second it was said
Connect Your Claude 
// your agent, any MCP runtime
-search_memories({
-  query: "what did we promise Ariika for phase 2?",
-  verification_strictness: "human_only"
-})
-
-// → 3 commitments · each confirmed by a named human
-// → source: client call 2026-06-02 · 0:14:32

Fair questions.

Q.Isn’t this another meeting notetaker?

Notetakers hand you a summary and stop. Knowcap is the layer after the summary: every extracted claim is confirmed by a named human, becomes part of your organization’s verified memory, and is served to your AI agents with an audit trail. Summaries are the input. Kept commitments are the output.

Q.Confirming every claim sounds like work.

It is about two minutes per meeting, one tap per claim. That is the entire human cost of agents that act on truth instead of guesses. And there is no “confirm all” button — by design. One bulk approve would poison the whole graph.

Q.What about our data?

Your graph is scoped to your organization. Agents see only what their API key allows, at the strictness tier you set. Every confirmation is logged: who, what, when, against which source. Built for Saudi PDPL and GDPR Article 22 from day one.

Q.Which tools does it work with?

Claude, Codex, and Gemini today via MCP. Capture from Google Meet, uploaded recordings, voice notes, documents, URLs, and Telegram. Odoo task creation for implementation teams.

Organizations aren’t hierarchies. They’re webs of commitments.

AI is finally able to make sure they’re kept.

Get Started Free Book a Demo
    \ No newline at end of file diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v5-product-led-light.html b/docs/brand/design-explorations/shotgun-2026-06-10/v5-product-led-light.html deleted file mode 100644 index f88b741..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v5-product-led-light.html +++ /dev/null @@ -1,916 +0,0 @@ - - - - - -V5 — Product-Led Light · Knowcap - - - - - - - - - - - -
    -
    -
    Knowcap · MCP server for Claude, Codex & Gemini
    - -

    Your company's deepest knowledge is its commitments and the risks against them. Knowcap makes sure they're kept.

    - -

    Your client was promised delivery by June. Your team lead promised the demo would work. Those promises live in conversations, and they die there. Knowcap captures every commitment spoken aloud, flags every risk against it, and lets your AI agents act on it — after a named human confirms it.

    - -
    Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true.
    - -
    - Get Started Free - Book a Demo -
    - -
    - Built by an Odoo partner - · - MCP-native - · - Full audit trail on every action -
    - - -
    - -
    -
    -
    - - -
    -
    -
    What dies in the conversation
    -

    The deadline slipped because the promise never lived anywhere.

    -

    A company makes hundreds of promises a week. To clients. To employees. To suppliers. None of them live in your project tool. They live in calls, voice notes, and chat threads. When one breaks, you find out last.

    - -
    -
    -
    01 · Client
    -

    The client promise

    -

    “We'll deliver by June.” Said on a Zoom call. Never made it into the SOW. The scope grew, the date didn't move, and the margin paid for it.

    -
    -
    -
    02 · Internal
    -

    The internal promise

    -

    “It'll be ready for the demo.” Said in standup. Slipped out of standup three weeks ago. The demo found out for you.

    -
    -
    -
    03 · Supplier
    -

    The supplier promise

    -

    “Lead time is four weeks.” Said on a phone call. Shipped in six. Your customer churned and your team never saw it coming.

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    That is not a project-management problem. It is an open loop. Knowcap closes it.

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    Listen. Extract. Confirm. Act.

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    Knowcap captures the conversations your team is already having: meetings, recordings, voice notes, documents, Telegram.

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    AI pulls out every commitment, decision, task, and risk. Each one carries its speaker and a timestamp back to the exact second it was said.

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    A named human reviews each claim and promotes it to evidence with one tap. No bulk approve. No silent ingestion. The graph holds what your team confirmed, nothing else.

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    Agents work from confirmed facts: draft the change-order email, create the Odoo task, brief the next meeting. Every action carries its receipts.

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    // Confirmation takes about two minutes per meeting. The agent actions it unlocks run before the meeting ends.
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    Organizations aren't hierarchies. They're webs of commitments.

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    AI is finally able to make sure they're kept.

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    Knowcap is verified knowledge for AI agents. Humans confirm. Agents act.

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    - - - - diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v6a-brass-product.html b/docs/brand/design-explorations/shotgun-2026-06-10/v6a-brass-product.html deleted file mode 100644 index 0b28ffa..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v6a-brass-product.html +++ /dev/null @@ -1,1257 +0,0 @@ - - - - - -V6a — Brass Dossier × Product Window · Knowcap - - - - - -
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    - ✓ - Knowcap · MCP Server for Claude, Codex & Gemini -
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    - Your company's deepest knowledge is its commitments and the risks against them.
    - Knowcap makes sure they're kept. -

    - -

    - Your client was promised delivery by June. Your team lead promised the demo would work. - Those promises live in conversations, and they die there. Knowcap captures every commitment - spoken aloud, flags every risk against it, and lets your AI agents act on it — - after a named human confirms it. -

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    - Most AI agents act on what the AI thinks is true. - Knowcap agents act only on what a human said is true. -
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    The deadline slipped because the promise never lived anywhere.

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    - A company makes hundreds of promises a week. To clients. To employees. To suppliers. - None of them live in your project tool. They live in calls, voice notes, and chat threads. - When one breaks, you find out last. -

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    Said on a Zoom call. Never made it into the SOW. The scope grew, - the date didn't move, and the margin paid for it.

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    Said in standup. Slipped out of standup three weeks ago. - The demo found out for you.

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    The supplier promise
    - “Lead time is four weeks.” -

    Said on a phone call. Shipped in six. Your customer churned - and your team never saw it coming.

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    - That is not a project-management problem. It is an open loop. - Knowcap closes it. -

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    Listen. Extract. Confirm. Act.

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    Knowcap captures the conversations your team is already having: meetings, - recordings, voice notes, documents, Telegram.

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    Extract

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    AI pulls out every commitment, decision, task, and risk. Each one carries its - speaker and a timestamp back to the exact second it was said.

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    A named human reviews each claim and promotes it to evidence with one tap. - No bulk approve. No silent ingestion. The graph holds what your team confirmed, - nothing else.

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    Act

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    Agents work from confirmed facts: draft the change-order email, create the - Odoo task, brief the next meeting. Every action carries its receipts.

    -
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    - Confirmation takes about two minutes per meeting. - The agent actions it unlocks run before the meeting ends. -

    -
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    - Organizations aren't hierarchies.
    - They're webs of commitments. -

    - -

    AI is finally able to make sure they're kept.

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    - Get Started Free - Book a Demo -
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    Knowcap is verified knowledge for AI agents. Humans confirm. Agents act.

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    - - - - - diff --git a/docs/brand/design-explorations/shotgun-2026-06-10/v6b-editorial-product.html b/docs/brand/design-explorations/shotgun-2026-06-10/v6b-editorial-product.html deleted file mode 100644 index df375bb..0000000 --- a/docs/brand/design-explorations/shotgun-2026-06-10/v6b-editorial-product.html +++ /dev/null @@ -1,1077 +0,0 @@ - - - - - -V6b — Editorial Light × Product Window · Knowcap - - - - - - - - -
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    - Knowcap · MCP server for Claude, Codex & Gemini - Knowcap - Vol. 01 — Commitments -
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    Your company’s deepest knowledge is its commitments and the risks against them. Knowcap makes sure they’re kept.

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    Your client was promised delivery by June. Your team lead promised the demo would work. Those promises live in conversations, and they die there. Knowcap captures every commitment spoken aloud, flags every risk against it, and lets your AI agents act on it — after a named human confirms it.

    - -
    - Doctrine -
    Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true.
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    - Get Started Free - Book a Demo -
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    - Built by an Odoo partner·MCP-native·Full audit trail on every action -
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    Fig. 01The inbox — a client commitment, the risk against it, and the one tap that lets agents act.
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    The deadline slipped because the promise never lived anywhere.

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    A company makes hundreds of promises a week. To clients. To employees. To suppliers. None of them live in your project tool. They live in calls, voice notes, and chat threads. When one breaks, you find out last.

    -
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    - № 1 — The client promise -

    “We’ll deliver by June.”

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    Said on a Zoom call. Never made it into the SOW. The scope grew, the date didn’t move, and the margin paid for it.

    -
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    - № 2 — The internal promise -

    “It’ll be ready for the demo.”

    -

    Said in standup. Slipped out of standup three weeks ago. The demo found out for you.

    -
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    - № 3 — The supplier promise -

    “Lead time is four weeks.”

    -

    Said on a phone call. Shipped in six. Your customer churned and your team never saw it coming.

    -
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    That is not a project-management problem. It is an open loop. Knowcap closes it.

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    Listen. Extract. Confirm. Act.

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    Listen

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    Knowcap captures the conversations your team is already having: meetings, recordings, voice notes, documents, Telegram.

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    Extract

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    AI pulls out every commitment, decision, task, and risk. Each one carries its speaker and a timestamp back to the exact second it was said.

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    Confirm

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    A named human reviews each claim and promotes it to evidence with one tap. No bulk approve. No silent ingestion. The graph holds what your team confirmed, nothing else.

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    Act

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    Agents work from confirmed facts: draft the change-order email, create the Odoo task, brief the next meeting. Every action carries its receipts.

    -
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    Confirmation takes about two minutes per meeting. The agent actions it unlocks run before the meeting ends.

    -
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    - Knowcap · The thesis -

    Organizations aren’t hierarchies.
    They’re webs of commitments.

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    AI is finally able to make sure they’re kept.

    -
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    - Get Started Free - Book a Demo -
    -
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    - - -
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    - Knowcap is verified knowledge for AI agents. Humans confirm. Agents act. - © 2026 Knowcap -
    -
    - - - - diff --git a/docs/brand/design-explorations/v3-variant-library.md b/docs/brand/design-explorations/v3-variant-library.md deleted file mode 100644 index f75fa0e..0000000 --- a/docs/brand/design-explorations/v3-variant-library.md +++ /dev/null @@ -1,119 +0,0 @@ -# Knowcap v3 — Variant "Library" - -The K in Knowcap stands for *knowledge*. This variant leans into that: warm parchment paper, oxblood accent, a touch of EB Garamond serif for display, and the surface treatment of a well-kept reference library — without going full 19th-century novel. - -**Critical:** The visual reference is `docs/mockups/library-v2.html` in this repo (open in a browser to see the exact rendering). NOT `library.html` — that was v1, too literal / too booky / too hard to read. v2 is the approved aesthetic: library DNA preserved, modern readable execution. - -Same IA, same 11 surfaces, same sidebar order as v3 baseline. Full verbatim component spec: `docs/v3-design-spec.md` (1,296 lines). - ---- - -## Field 1 — Company name and blurb (paste into the first textarea) - -Knowcap is meeting intelligence with a librarian's discipline. The K in our name stands for *knowledge* — we treat every claim from a meeting like a citation in a reference work. Record meetings, calls, and screen sessions; transcribe via Whisper + Pyannote diarization; extract verified claims (facts, risks, decisions, tasks, people) via Gemini 2.5 Pro. Every claim has a speaker, a timestamp, a source — re-verifiable, queryable. 11 surfaces, sidebar-driven, three organizations (Knowcap, Ariika, SMEtools). Design direction is "library" — warm parchment paper #F5EBDC background, oxblood accent #8B3E2F, EB Garamond serif for the K-mark logo + surface titles + claim headlines, Geist Sans for body copy at 14.5px. Modern card-based layout with a thin oxblood accent stripe on each claim card (the "book spine" gesture). NOT a heavy book pastiche — readable, modern, restrained. Reference mockup: docs/mockups/library-v2.html. - ---- - -## Field 2 — GitHub repo - -https://github.com/Knowcap-V2/knowcap - ---- - -## Field 3 — Any other notes (paste into the second textarea) - -DESIGN DIRECTION: "Library" — knowledge / reference / warm parchment, modern execution. - -**Critical:** Visual reference is `docs/mockups/library-v2.html` in this repo. Open it in a browser to see exact rendering. There is also an earlier `docs/mockups/library.html` — DO NOT use that as reference, it's too literal / too dense serif / too theatrical. v2 is the approved version. - -## Aesthetic posture -- The K in Knowcap = knowledge. Library / reference-work DNA. -- Warm parchment + oxblood accent — NOT the cream + Space Grotesk baseline. -- Modern card layout, generous whitespace, restrained serif touch. -- Light mode only for the initial design (no dark twin in this variant). -- Restrained, readable, librarian-grade. NOT a 19th-century novel pastiche. - -## Typography -- Display + K-mark + surface titles + claim headlines: **EB Garamond** (free on Google Fonts) — weights 500, 600, 700 only. -- Body / nav / meta / quotes / labels: **Geist Sans** (free on Google Fonts, distinctive, very readable) — weights 300, 400, 500, 600, 700. -- NO mono font in chrome (only on /developers code chips, JetBrains Mono). -- NEVER Inter, Roboto, Arial, Space Grotesk. AI-slop fonts. -- Body size 14.5px line-height 1.55. Headlines 21px (claim) and 44px (surface title). Display weight 600, never lighter. - -## Color palette -- Parchment (page bg): #F5EBDC (warm cream) -- Parchment-2 (sidebar bg): #EFE3CF (slightly warmer) -- Card / surface: #FBF4E5 (cream paper card) -- Rule lines: #D9C9A8 (warm rule) -- Ink (foreground): #2D1F18 (warm dark, NOT pure black) -- Ink-muted: #6B584A -- Ink-dim: #998470 -- **Accent: #8B3E2F (oxblood)** — used for: active sidebar left-bar (2px), claim card left-edge stripe (default), tab underline on active, AI-prediction badge bg, K-mark color -- Soft oxblood (badge bg): #F2DCD3 -- Category accents (used as per-card left-edge stripe + cat badge bg): - - Fact: #1F6B3A on #DCEBE0 (Knowcap green) - - Risk: #9B1D1D on #F5DDD9 - - Decision: #4A2FA8 on #E5DEF7 (Ariika purple) - - Task: #1B4F8F on #DCE7F2 - - People: #8A5A12 on #F2E4C7 (SMEtools amber) -- Org dots in workspace switcher: oxblood (All), green (Knowcap), purple (Ariika), amber (SMEtools) - -## Layout (Inbox surface) -- AppLayout: 240px sidebar + main flex-1. -- Sidebar: K-mark serif + "Knowcap" wordmark with "v3 · library" subtitle, then a Workspace switcher (4 rows: All / Knowcap / Ariika / SMEtools), then 4 grouped nav sections (Work / Knowledge / Automate / More). Each nav link has a 2px transparent left border that becomes oxblood on active state. Active link also gets a cream-paper card background. -- Main canvas: max-width 1080px, generous left/right padding. -- Surface header: tiny crumb ("All organizations · Inbox") then big serif title "Inbox" then a sans deck explaining today's state. -- Toolbar: 5 underline-style tabs (To do / Confirmed / All / Agents / Noise) with the active tab in oxblood. Right side has "Importance ↓" and "Search" pills. -- Card list: each claim is a card with: - - 3px left edge stripe colored by category (or oxblood as default) - - Category small-caps badge at top + org/project chip beside it - - Serif headline (21px EB Garamond 600) - - Italic sans quote (14px) - - AI-prediction line: oxblood-soft "Predicted route" / "Auto-routed" / "Awaiting route" badge + project name - - Meta column on the right: speaker (bold), `@ HH:MM` timestamp (tabular nums), source name (dim) -- Footer colophon: "K · Knowcap · Inbox" — tiny, centered, italic K. - -## Other surfaces — apply the same vocabulary -- **/sources** = "Archive". Same card-list pattern, columns adapted. -- **/claims** = "Library" (yes, literally — the library inside Library). Same card pattern, category-colored stripe per claim. -- **/projects** = card grid, oxblood headers. -- **/rules** = a markdown editor on parchment. Looks like writing rules in a leather-bound notebook. -- **/agents** = author-card grid for Definitions; routine cards for Routines. -- **/atlas** = soft constellation on parchment, oxblood lines. -- **/integrations** = card grid, parchment. -- **/developers** = long-form reference layout. EB Garamond headings, Geist body, JetBrains Mono code blocks. -- **/ask** = a single column of conversation. User questions in roman sans, assistant answers in EB Garamond italic with numbered footnote citations. -- **/home** = "Today's reading" with greeting + stats. - -## Motion -- Page transitions: 200ms cross-fade. -- Hover state on cards: subtle bg shift (cream → warmer cream), no shadow change. -- Active tab underline animates in. - -## Vocabulary (light library touch) -Keep the v3 baseline vocabulary mostly intact (Inbox, Sources, Claims, Projects, Rules, Agents, Atlas, Integrations, Developers, Home, Ask Knowcap). Don't replace them with "Today's briefing" / "Archive" — that was the rejected Quarterly direction. Library uses normal Knowcap nouns, just rendered on parchment with serif touches. - -The ONE place where vocabulary leans library: -- Tiny footer colophon on every surface: "K · Knowcap · " -- /developers landing has a chapter-style numbering on its sub-sections - -## What NOT to do -- No bookshelf-as-sidebar (rejected — too literal) -- No Roman numerals on entries (rejected — too booky) -- No "Chapter IV — Inbox" theatrics (rejected — overdone) -- No marginalia column on Inbox rows (rejected — hard to read) -- No EB Garamond on body copy (rejected — fatiguing) -- No "ye olde" tone in microcopy - -## Build order -1. Tokens + parchment palette + Geist Sans / EB Garamond pairing -2. AppLayout shell with workspace switcher + grouped sidebar -3. Inbox as approved (card list with category-colored left stripe) -4. Sources, Claims, Projects, Atlas as variations of the same card pattern -5. Rules editor on parchment -6. Agents Routines + Definitions -7. Ask Knowcap as serif-italic conversation -8. Integrations + Developers + Home - -## IA reference -Same 11 surfaces, same sidebar order as v3 baseline. Full verbatim component spec at `docs/v3-design-spec.md` in this repo. Visual reference: `docs/mockups/library-v2.html`. diff --git a/docs/brand/design-explorations/v3-variant-operator-light.md b/docs/brand/design-explorations/v3-variant-operator-light.md deleted file mode 100644 index ab4fe87..0000000 --- a/docs/brand/design-explorations/v3-variant-operator-light.md +++ /dev/null @@ -1,122 +0,0 @@ -# Knowcap v3 — Variant "Operator (Light)" - -The **light-mode twin** of the Operator variant. Same terminal/keyboard-first power-software DNA — single-letter sidebar shortcuts, dense table-first surfaces, always-visible status bar, ⌘K command palette, Vim-style filter chips — but rendered on warm paper instead of soft-black. - -This is NOT the v3 baseline (which is editorial-cream + Space Grotesk sans). This is the Operator aesthetic *in light mode*: still monospace, still keyboard-first, still dense — but inhabitable in daylight. - -**Reference mockup in this repo:** `docs/mockups/operator-light.html` (live HTML, open in browser to see exact rendering). Companion dark version: `docs/mockups/operator.html`. - -Same IA, same 11 surfaces, same sidebar order as v3 baseline. Full verbatim component spec: `docs/v3-design-spec.md` (1,296 lines). - ---- - -## Field 1 — Company name and blurb (paste into the first textarea) - -Knowcap is power software for operators — meeting intelligence built for people who live in the keyboard. We record meetings, calls, and screen sessions; transcribe via Whisper + Pyannote diarization; extract verified claims (facts, risks, decisions, tasks, people) via Gemini 2.5 Pro. Every claim has a speaker, a timestamp, and a source — re-verifiable, queryable, scriptable. 11 surfaces, sidebar-driven, three organizations (Knowcap, Ariika, SMEtools). Design direction: terminal / keyboard-first operator aesthetic IN LIGHT MODE — warm off-white background #FAFAF7, dark slate foreground, JetBrains Mono throughout, single-letter sidebar shortcuts, status bar always visible, ⌘K command palette, Vim-style filter chips (`!todo`, `:speaker:khaled`), filled v3 category badges (FAC green, RSK red, DEC purple, TSK blue, PPL amber). Knowcap green #1F6B3A as the accent. Think Sublime Text light theme × Linear's keyboard DNA × a working operator console. Reference mockup: docs/mockups/operator-light.html in the repo. - ---- - -## Field 2 — GitHub repo - -https://github.com/Knowcap-V2/knowcap - ---- - -## Field 3 — Any other notes (paste into the second textarea) - -DESIGN DIRECTION: "Operator (Light)" — terminal aesthetic, light mode. - -**Critical:** This is the LIGHT-MODE twin of the Operator variant. Visual reference is `docs/mockups/operator-light.html` in the repo — open it in a browser to see exact rendering. Companion dark version at `docs/mockups/operator.html`. Both share the same structure; only the palette flips. - -## Aesthetic posture -- Terminal / keyboard-first power software, rendered for daylight. -- NOT the v3 baseline (which is editorial-cream + Space Grotesk). This is monospace-everything. -- Dense. Table-first. Status bar always visible. Every action discoverable via ⌘K. -- Single-letter sidebar shortcuts. ⌘K is the front door. -- Looks like a tool, not a website. - -## Typography -- Display + body: **JetBrains Mono** (free on Google Fonts). All weights — 400, 500, 600, 700. -- Heading scale = weight differentiation. No serif in chrome. -- ONE exception: the K-mark logo in **Instrument Serif** (Google Fonts, free) — rendered in Knowcap-green for a moment of contrast. -- NEVER Inter, Roboto, Arial, Space Grotesk. They are AI-slop fonts. - -## Color palette -- Background: #FAFAF7 (warm off-white, NOT pure white) -- Surface (sidebar, status bar): #F2F0EA (one step warmer) -- Surface-2 (raised): #EAE7DF -- Border subtle: #DDD8CC -- Border strong (chips, divider): #C8C2B2 -- Foreground: #18181B (near-black slate) -- Dim foreground: #5B5B62 -- Dimmer (less important text): #8B8B91 -- **Accent: #1F6B3A (Knowcap green)** — used for: active sidebar highlight, prompt cursor, prompt path, "active filter" chip outline, status-bar branch indicator, timestamp links -- Filled v3 category badges (NOT outlined — solid pills for light-mode contrast): - - Fact: #1F6B3A on #E6F4EA (green pill) - - Risk: #9B1D1D on #FCE8E6 (red pill) - - Decision: #4A2FA8 on #ECE7FB (purple pill) - - Task: #1B4F8F on #DCEEFB (blue pill) - - People: #8A5A12 on #FBEFD8 (amber pill) -- Org chips kept as v3 brand: - - Knowcap (kc): #1F6B3A green - - Ariika (ar): #4A2FA8 purple - - SMEtools (sm): #8A5A12 amber - -## Layout (identical to Operator dark) -- Sidebar **56px wide**, single-letter shortcuts vertically: `i a s c p r g x n d h` -- Logo at top: K-mark in Instrument Serif, Knowcap green -- Active nav row: green-tinted background + green left border (2px) -- Top bar (34px): breadcrumb `knowcap / inbox · all-orgs`, ⌘K hint pill on the right -- Main canvas: prompt line `~/knowcap/inbox $ ▊` (blinking cursor), surface title with meta count, filter chips row, dense table -- Filter chips: `!todo`, `!confirmed`, `!all`, `!agents`, `!noise` (bang prefix) and `:speaker:khaled`, `:org:knowcap`, `:after:2026-05-01` (colon prefix) -- Dense table columns: cat (filled badge), org/project (colored chip + name), quote (full text), speaker, @ (timestamp in green), source-id (dimmer) -- Status bar (26px) always visible at bottom: `● all-orgs/inbox · 12 rows · filter: !todo` on left, `j k nav · ⌘K palette · ? help` on right with kbd-style boxes - -## Motion -- Cursor blinks in prompt and in command palette. -- No transitions on navigation — instant. Operators don't want to wait. -- Status bar updates flicker subtly when state changes. -- Hover state: faint border-strong flash, no shadows. - -## The one memorable thing -The prompt line at the top of every screen: - -``` -~/knowcap/[surface] $ ▊ -``` - -Blinking green cursor. Instantly readable as "this is a tool, not a website." When ⌘K is invoked, the prompt expands into a real input. - -## Vocabulary (terminal-flavored, identical to dark) -- Inbox = "inbox" -- Sources = "sources" -- Claims = "claims" -- Projects = "projects" -- Rules = "rules" (think .rc config files) -- Agents = "routines" -- Atlas = "graph" -- Integrations = "plugins" -- Developers = "sdk" -- Home = "status" - -## Build order -1. Light-mode tokens + JetBrains Mono everywhere + Instrument Serif K-mark -2. AppLayout shell: 56px sidebar + 34px topbar + 26px status bar -3. CommandPalette as the canonical entry point — the front door -4. Inbox as dense expandable table (this is the hero surface; nail it first) -5. Sources as dense table with bang/colon filters -6. Claims as grep-output stream with category-color line prefixes -7. Rules as monaco-style markdown editor with ex-mode commands -8. Agents Routines + Definitions as `man`-page entries -9. Atlas — light variant of constellation (subtle dots on paper) -10. Ask Knowcap — terminal-interview style with citation `[1]` links -11. Integrations / Developers / Home as ref-doc layouts - -## Pair with dark -Design the toggle from the start. Light is default, but `theme:dark` flips to: -- bg #0B0E14 -- fg #C9D1D9 -- accent #58A6FF (electric blue) -- category badges become outlined ANSI (bright green/amber/magenta/cyan/orange) - -See `docs/mockups/operator.html` for the dark version of every element. diff --git a/docs/brand/design-explorations/v3-variant-operator.md b/docs/brand/design-explorations/v3-variant-operator.md deleted file mode 100644 index 94310ea..0000000 --- a/docs/brand/design-explorations/v3-variant-operator.md +++ /dev/null @@ -1,114 +0,0 @@ -# Knowcap v3 — Variant "Operator" - -Terminal / keyboard-first power-software aesthetic. The thesis: Knowcap is *for operators* — people who think in shortcuts, live in dark mode, and want every screen to tell them how to drive it without a mouse. Reference points: Linear's keyboard DNA × Bloomberg terminal × Vercel CLI. - -Same IA, same 11 surfaces, same sidebar order as the v3 baseline. Source-of-truth spec: `docs/v3-design-spec.md` (1,296 lines, verbatim component extraction). This file overlays a different aesthetic vocabulary on top. - ---- - -## Field 1 — Company name and blurb (paste into the first textarea) - -Knowcap is power software for operators. We record meetings, calls, and screen sessions; transcribe via Whisper + Pyannote diarization; extract verified claims (facts, risks, decisions, tasks, people) via Gemini 2.5 Pro. Every claim has a speaker, a timestamp, and a source — re-verifiable, queryable, scriptable. 11 surfaces, sidebar-driven, three organizations (Knowcap, Ariika, SMEtools). Design direction is terminal / keyboard-first operator aesthetic — JetBrains Mono everywhere except long-form, soft-black background #0B0E14, dense table-first layout, status bar always visible, single-letter sidebar shortcuts, Vim-style command palette, every action has a binding. Think Linear's keyboard DNA × Bloomberg terminal × Vercel CLI. Built for people who live in the keyboard. - ---- - -## Field 2 — GitHub repo - -https://github.com/Knowcap-V2/knowcap - ---- - -## Field 3 — Any other notes (paste into the second textarea) - -DESIGN DIRECTION: "Operator" — terminal, keyboard-first, dense. - -## Aesthetic posture -- Linear keyboard DNA × Bloomberg terminal × Vercel CLI. -- Dark by default; light mode supported but feels secondary. -- Dense. Table-first. Status bar always visible. Every action discoverable via ⌘K. -- Monospace dominates. Single-letter shortcuts shown next to every sidebar item. -- The product looks like a tool, not a website. - -## Typography -- Display + body: **JetBrains Mono** (free, open-source, on Google Fonts — Berkeley Mono is paid and would trigger the brand-fonts warning, skip it). -- Heading scale: only weights vary (JetBrains Mono regular / bold / extra-bold / italic). No serif in chrome. -- ONE exception: the K-mark logo in a short serif (**Instrument Serif** on Google Fonts — free) for one moment of contrast. -- NEVER Inter, Roboto, Arial, Space Grotesk. - -## Color palette -- Background: #0B0E14 (soft black, not pure black) -- Surface: #11151D (one step up) -- Foreground: #C9D1D9 (warm white) -- Dim foreground: #8B949E -- Subtle border: #1F2530 -- Accent (cursor, primary action, active focus): #58A6FF (soft electric blue) -- Category-as-ANSI: - - Fact: #3FB950 (bright green) - - Risk: #D29922 (amber) - - Decision: #BC8CFF (magenta) - - Task: #79C0FF (cyan) - - People: #FF7B72 (orange) -- Org accents repurposed as ANSI-style chips: - - Knowcap: #3FB950 (green) — kept - - Ariika: #BC8CFF (magenta) — shifted from purple to ANSI magenta - - SMEtools: #D29922 (amber) — kept - -## Layout -- Sidebar **44px collapsed** (icon + single-letter shortcut), **220px expanded**. Defaults to collapsed. -- Single-letter shortcut visible next to every nav item: - `i` Inbox · `a` Ask · `s` Sources · `c` Claims · `p` Projects · `r` Rules · `g` Agents · `x` Atlas · `n` Integrations · `d` Developers · `h` Home -- Main canvas full-width, dense table-first. -- **Status bar always visible at bottom (24px)**: cursor position, row count, filter expression, ⌘K hint, branch indicator (org/project context). -- Top bar minimal: breadcrumb + ⌘K hint, no logo. -- **InboxRow** renders as a single dense table row, expandable inline. Keys `j/k` navigate, Enter expands, ⌘Enter routes to project. -- **Sources** = dense virtualized table. Vim-style filter chips: `!recording`, `:speaker:khaled`. -- **Claims** = grep-output style. Each line: `[CATEGORY] org/project · "quote" · speaker @ 14:23 · source-id`. -- **Rules** = full-screen monaco-style editor; `:w` to save; `?` for help overlay. -- **Agents Definitions** = `man`-page-style entries: section headers, dense prose, code blocks. -- **Atlas** Constellation variant promoted (suits dark aesthetic). When sidebar collapsed, Atlas falls back to ASCII-art constellation rendering. -- **Ask Knowcap** = terminal prompt at top, response in monospace, citations as `[1]` links. -- **Developers** = command-reference layout. -- **Home** = today's status dashboard, all numbers mono. - -## Motion -- No transitions on navigation — instant. Operators don't want to wait. -- Cursor blinks in command palette. -- Status bar flickers subtly when state changes (one frame). -- Hover state: faint single-pixel border flash. No drop shadows. - -## Vocabulary (terminal-flavored) -- Inbox = "inbox" -- Sources = "sources" -- Claims = "claims" -- Projects = "projects" -- Rules = "rules" (think `.rc` config) -- Agents = "routines" (cron-like) -- Atlas = "graph" -- Integrations = "plugins" -- Developers = "sdk" -- Home = "status" - -## The one memorable thing -Every screen has a tiny prompt-style header in the top-left: - -``` -~/knowcap/[surface] $ _ -``` - -Blinking cursor. Instantly readable as "this is a tool." When you focus the command palette (⌘K), the prompt expands to a real input field. - -## Build order -1. Tokens + Berkeley Mono everywhere + soft-black palette -2. AppLayout shell with 44px collapsed sidebar + 24px status bar -3. CommandPalette as the canonical entry point — this is the front door -4. Inbox as dense expandable table -5. Sources as grep-output stream -6. Claims as grep-output stream with category-color line prefixes -7. Rules as monaco-style editor with ex-mode commands -8. Agents Routines + Definitions as `man`-page entries -9. Atlas Constellation (dark) + ASCII fallback -10. Ask Knowcap as terminal interview -11. Integrations / Developers / Home as ref docs - -## IA reference -Same 11 surfaces, same sidebar order as v3 baseline. Full verbatim component spec at `docs/v3-design-spec.md` in this repo. diff --git a/docs/brand/design-explorations/v3-variant-quarterly.md b/docs/brand/design-explorations/v3-variant-quarterly.md deleted file mode 100644 index d1eb459..0000000 --- a/docs/brand/design-explorations/v3-variant-quarterly.md +++ /dev/null @@ -1,99 +0,0 @@ -# Knowcap v3 — Variant "Quarterly" - -Editorial / publication aesthetic. The thesis: every claim is a verified quote, treated with the typographic respect of a magazine column — not a database row. We are designing for *product readers*, not product users. Reference points: The Atlantic, Stratechery, Bloomberg Briefs. - -Same IA, same 11 surfaces, same sidebar order as the v3 baseline. Source-of-truth spec: `docs/v3-design-spec.md` (1,296 lines, verbatim component extraction). This file overlays a different aesthetic vocabulary on top. - ---- - -## Field 1 — Company name and blurb (paste into the first textarea) - -Knowcap is meeting intelligence in the language of journalism. We record meetings, calls, and screen sessions; transcribe via Whisper + Pyannote diarization; extract verified claims — facts, risks, decisions, tasks, people — through Gemini 2.5 Pro. Every claim is a quote attributed to a speaker at a precise timestamp, citable and re-verifiable like a magazine article. The product reads like a daily briefing: an Inbox of incoming claims awaiting your routing, an Archive of Sources, a Library of cross-org Claims, and a set of Rules + Agents that shape what enters the record. 11 surfaces, sidebar-driven, three organizations (Knowcap, Ariika, SMEtools). Design direction is editorial / publication — Fraunces or GT Sectra display, Söhne or Inter Tight body, ink on warm paper, asymmetric grid, drop caps, footnote-style citations, single accent terracotta #C8553D. - ---- - -## Field 2 — GitHub repo - -https://github.com/Knowcap-V2/knowcap - ---- - -## Field 3 — Any other notes (paste into the second textarea) - -DESIGN DIRECTION: "Quarterly" — editorial / publication. - -## Aesthetic posture -- Magazine-grade. The Atlantic / Stratechery / Bloomberg Briefs. -- Restraint. Generous whitespace. Wide left margins. Optical alignment. -- Asymmetric grids. Drop caps. Pull-quotes. Footnote-style citations. -- Light mode is primary; dark mode supported but feels "evening read" not "code editor." - -## Typography -- Display: **Fraunces** (variable, optical-size aware — free on Google Fonts). NO fallback to GT Sectra or Recoleta; those are paid and would trigger the brand-fonts warning. -- Body: **Instrument Sans** (free on Google Fonts — clean, modern, refined; works as a Söhne stand-in without the paid-font warning). Söhne is paid, skip it. -- Mono: JetBrains Mono — used ONLY in code chips on /developers, never in chrome. -- NEVER Inter, Roboto, Arial, Space Grotesk. They are AI-slop fonts. - -## Color palette -- Paper: #F8F4EC (warm cream) -- Ink: #0A1628 (deep navy) -- Muted ink: #4A5468 -- Rule lines: #D9D2C2 (warm paper rule) -- Accent: #C8553D (terracotta) — used very sparingly: active sidebar item, primary action, citation chip -- Org tags (demoted to small inline pills, not heroes): - - Knowcap: #1F6B3A green (kept) - - Ariika: #4A2FA8 purple (kept) - - SMEtools: #B5731A amber (kept) -- Category badges rendered as serif-bold small caps on tinted paper, not pill chips. - -## Layout -- Sidebar 240px, paper background. Top is a "Volume III · Issue 47" masthead with today's date in small caps. -- Main canvas max-width ~960px, generous gutters. -- **Inbox** = daily briefing. Each InboxRow looks like a column entry: bold serif source title, italic AI prediction, indented blockquote for the top claim, footnote-numbered citations beneath. -- **Sources** = archive. Single column of dated entries, like a periodical's back-issue index. -- **Claims** = library. Each claim is a pull-quote in serif italic, citation in small-caps beneath. Filters at top read like a card catalog. -- **Ask Knowcap** = embedded interview. User question in roman, assistant answer in serif, citations as drop-down footnotes [1] [2] [3]. -- **Rules** = full-screen markdown editor, paper background, looks like an essay draft. -- **Agents Definitions** catalog = author cards with portrait wells. -- **Atlas** Library variant promoted; Constellation variant deprioritized. -- **Developers** = a printed manifesto. -- **Home** = today's briefing, signed by the editor. - -## Motion -- Page transitions: slow cross-fade, not slide. -- Hover states: subtle ink-color shift, no drop shadows. Citation numbers underline on hover. -- Scroll-triggered: drop caps fade in once when a section enters viewport. - -## Vocabulary (verb-free, masthead-flavored) -- Inbox = "Today's briefing" -- Sources = "Archive" -- Claims = "Library" -- Projects = "Beats" -- Rules = "Style guide" -- Agents = "Columnists" -- Atlas = "Index" -- Integrations = "Wire services" -- Developers = "Pressroom" -- Home = "Masthead" - -## The one memorable thing -Every claim card has a small-caps masthead-style attribution at the top: - -> VOLUME III · ISSUE 47 · 2026 · SOURCE: *Q1 Board Sync* · SPEAKER: Khaled · MINUTE 14:23 - -Treat every claim like a citation in a printed journal. - -## Build order -1. Tokens + type system + paper/ink palette -2. AppLayout shell with masthead sidebar -3. Inbox as daily briefing (highest signal of the aesthetic) -4. Sources as archive -5. Claims as library -6. Ask Knowcap as embedded interview -7. Rules as essay -8. Agents Definitions as author cards -9. Atlas Library variant -10. Integrations + Developers + Home as long-form pages - -## IA reference -Same 11 surfaces, same sidebar order as v3 baseline. Full verbatim component spec at `docs/v3-design-spec.md` in this repo. diff --git a/docs/brand/legacy/brand-positioning-feb2026.md b/docs/brand/legacy/brand-positioning-feb2026.md deleted file mode 100644 index 300c0ad..0000000 --- a/docs/brand/legacy/brand-positioning-feb2026.md +++ /dev/null @@ -1,49 +0,0 @@ -# Brand Positioning - -**Current positioning (Feb 2026):** AI-powered governance layer for professional services. Visual + audio meeting transcription with persistent project memory. - -## The 5-Element Brand Framework - -Confirmed Feb 2026 in landing page design session (Hassan, Omar, Ismail, Ziad). Five pillars structure both the product and the marketing narrative. - -| Pillar | What it means | Competitor gap | -|---|---|---| -| **Governance** | Team audit, compliance, accountability | Most note-takers ignore this | -| **Agents** | AI agent that attends meetings and acts | Fireflies/Otter just transcribe | -| **Artifacts** | HTML-based generated documents (reports, dashboards, guides) | Competitors output text summaries only | -| **Memory** | Persistent project memory across sessions | Competitors are session-based | -| **Intelligence** | Contextual AI querying across all sources | Competitors don't connect across meetings | - -These five become section headers on the landing page, recurring beats in ad creative, and the structure for the animated event video. - -## Positioning Evolution - -| Phase | Date | Positioning line | -|---|---|---| -| 1 | Sep 2025 | "AI-powered project governance for professional services" | -| 2 | Oct 2025 | "AI knowledge & context engineering" — Loom + Awesome Screenshot + NotebookLM | -| 3 | Oct 2025 | "CEO's command center" — leadership / strategic angle | -| 4 | Nov 2025 | "Strategic partner for service firms" — visual transcription + project brain | -| 5 | Feb 2026 | "AI governance layer" — five-element framework | - -Pattern: positioning has narrowed from broad "governance" to the specific 5-element framework. Fragmentation risk — pick one and stay there for paid media. - -## Differentiators (for ad copy) - -- Visual + audio transcription (vs Fireflies/Otter — audio only) -- Persistent project memory (vs session-based competitors) -- HTML artifacts (vs text summaries) -- Arabic language support (regional moat for MENA) -- Team audit / governance layer - -## Brand Assets - -- **Name:** Knowcap (also: KnowCap, Knowcap.ai) -- **Domains:** `knowcap.ai` (marketing), `app.knowcap.ai` (product) -- **Logo:** Stylized "K" — geometric / interconnected pathways variant chosen Sep 2025 -- **Mission:** Eliminate project amnesia and transform team collaboration - -## Source notes -- `vibe/llm-wiki/wiki/Knowcap/topics/Knowcap Brand Identity and Positioning.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2026-02-12 - Landing Page Design Strategy Discussion.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/knowcap identity/2025-09-11 - Knowcap.ai Brand Identity Guide.md` diff --git a/docs/brand/legacy/icp-segments-oct2025-stratdev.md b/docs/brand/legacy/icp-segments-oct2025-stratdev.md deleted file mode 100644 index ef326b5..0000000 --- a/docs/brand/legacy/icp-segments-oct2025-stratdev.md +++ /dev/null @@ -1,29 +0,0 @@ -# Target Segments - -ICP map confirmed with StratDev (Oct 2025) and Hassan's own deal pipeline. - -## Primary Segments - -| Segment | Size signal | Why they buy | -|---|---|---| -| **Social media agencies** | 5–30 employees | Governance + meeting recap across many client accounts | -| **Odoo partners / ERP implementers** | 10–200 employees | Visual transcription + project memory cuts implementation rework | -| **Operations managers / COOs** | Professional services firms | Cross-departmental intelligence, root-cause for missed targets | -| **Sales managers** | Agencies, B2B services | Meeting audit ("is the team following the business plan?") | -| **CRM partners** | 10–100 employees | Cross-client knowledge that doesn't live in the CRM | -| **Consultants / accounting firms** | Boutique to mid-size | Repeatable engagement memory across long projects | - -## Messaging Strategy - -Segment-specific messaging tested independently in Meta — algorithm optimizes based on conversion. One generic landing page first, segment-specific landing pages after 4–6 weeks of paid data. - -Creative angles to test per segment: -- Governance / accountability -- Team audit ("are they following the plan?") -- Remote team management -- SOP generation -- Sales team monitoring - -## Source notes -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2025-10-27 - Stardev Kickoff Meeting.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2025-10-20 - Knowcap x StartDev.md` diff --git a/docs/brand/memory-ontology.html b/docs/brand/memory-ontology.html deleted file mode 100644 index b7cebd5..0000000 --- a/docs/brand/memory-ontology.html +++ /dev/null @@ -1,461 +0,0 @@ - - - - - -Knowcap — Memory Ontology (Levels + Fields) - - - -
    - -

    Knowcap — Memory Ontology Target state

    -

    The version we build toward. Layer 1 = the speech-act (what the classifier picks, one per memory). Layer 2 = the fields, in six homes. Org meaning + allowed values are set in organization.md.
    No typed field is hard-required — the meeting may not say it. The extractor tries to fill every field; a human completes gaps on confirm.

    - - -

    Layer 1 · The category (one per memory) — 4 the agents act on + 1 reference

    -
    -
    - Decision -
    what we chose
    -
    closes via superseded_by
    -
    → logs the choice, fires downstream routines (the Odoo demo)
    -
    -
    - Task -
    what we'll do
    -
    closes via completed_by
    -
    → create / sync to Odoo · GitHub · chase owner
    -
    -
    - Commitment -
    what we owe someone else
    -
    closes via fulfilled_by / breached_at
    -
    → the SOW baseline · scope-creep is measured against it
    -
    -
    - Risk -
    what threatens what we owe
    -
    closes via mitigated_by
    -
    → open register, escalate, re-quote (scope creep)
    -
    -
    - Note -
    reference / context
    -
    no closing edge
    -
    → agents READ it as grounding, never act on it
    replaces today's fact + general
    -
    -
    - - -

    Layer 2A · Universal — on every memory, every category

    -
    - Provenance (intrinsic) - Dimension (cross-cutting) - Ranking scalar - Lifecycle (derived) - Trust gate -
    -
    -
    -
    Provenance — who said it, where, when (immutable, the grounding)
    -
    - speakerwho uttered it - sourcerecording · doc · chat · email - timestamp(mm:ss) deep-link - created_atwhen extracted -
    -
    -
    -
    Dimensions — cross-cutting, many per memory, you filter/join on these
    -
    - entities[]persons / orgs REFERENCED - topics[]crosscut tags (org vocab) -
    -

    speaker ≠ entities. Speaker = who said it. Entities = who it's about.

    -
    -
    -
    Ranking — two different scalars, never merged
    -
    - importanceSYSTEM — claim → evidence score (0–2) - prioritywhat the person SAYS or we INFER · low·med·high·urgent -
    -
    -
    -
    Lifecycle — DERIVED from edges, never typed by hand
    -
    - statusopen · done · mitigated · fulfilled · superseded — computed -
    -

    Today status is a free-text box ("open"). Target: it's read-only, set by confirming a closing edge.

    -
    -
    -
    Trust gate — the moat
    -
    - review_statuspending · confirmed · edited · rejected - confirmed_bynamed human (audit) - confirmed_at -
    -
    -
    - - -

    Layer 2B · Per-category typed fields (orange = typed, only exist on that category · all best-effort extracted, none hard-required)

    -
    - - -
    -
    Decision"We agreed to build a centralized KB for the AI agents"
    -
    -
    decided_byHassan Arslan — who made the call
    -
    rationalewhy — the reasoning captured
    -
    decided_on newdate of the decision
    -
    supersedesedge → the decision this overrides
    -
    -
    - - -
    -
    Task"Build the centralized knowledge base"
    -
    -
    assigneewho does the work
    -
    deadlineinternal due date
    -
    completed_byedge → closes when work is done
    -
    fulfillsedge → the commitment this helps deliver
    -
    -
    - - -
    -
    Commitment new"We'll deliver the inventory module to ACME by Jun 30 (SOW line 12)"
    -
    -
    all optional — extractor works hard to capture them
    -
    promisorwho owes (us)
    -
    promiseewho is owed (the client) — cross-org
    -
    duethe promised date — drives breach
    -
    deliverablewhat D was promised
    -
    source_refSOW / quotation line it traces to
    -
    fulfilled_by / breached_atedge → counterparty + clock close it
    -
    -
    - - -
    -
    Risk"Client wants custom reports — not in the quotation" (scope creep)
    -
    -
    severityorg-defined: minor · blocking …
    -
    mitigationthe plan to close it
    -
    likelihood newoptional — register-grade scoring
    -
    threatens newlink → the commitment at risk (scope-creep source)
    -
    mitigated_byedge → closes when handled
    -
    -
    - - -
    -
    Note"Budget is $50k" · "Team has 5 members"
    -
    -
    valuethe fact's value, if any
    -
    unit new$, people, % …
    -
    contextsupporting detail
    -
    contradicted_byedge → a newer note that overrides it (staleness)
    -
    -
    - - -
    -
    organization.mdthe umbrella — per-org, no migration
    -
    -
    controls (per org)
    -
    semantics"risk = scope creep" (Odoo) vs "adverse precedent" (law)
    -
    allowed valuesrisk.severity enum, priority labels, status vocab
    -
    topics vocabthe org's tag taxonomy
    -
    hardcoded (universal)
    -
    the 5 categoriesorgs can't add categories
    -
    which fields existtask HAS deadline; risk HAS severity
    -
    edge types + statusthe lifecycle machinery
    -
    -
    - -
    - - -

    The shape of an organization — your model

    -

    An organization is a web of commitments — between employees & managers, and to third parties. Commitments carry risks; risks are mitigated by tasks & decisions; those tasks also fulfil the commitments. Notes are the facts it all stands on.

    - -
    -
    -
    Commitment
    -
    - employee ↔ manager→ third party (SOW) -
    -
    -
    ▼  comes with
    -
    Risk — threatens the commitment
    -
    ▼  mitigated by  ·  which also fulfils the commitment
    -
    - Task does the work - Decision sets the direction -
    -
    - Note — the verified facts everything above reasons over -
    -
    - - -

    Worked examples — real Ariika memories (2 per category · pulled live from Knowcap · each card shows Layer 2A + 2B together)

    - - -
    -
    Decision
    -
    -
    -
    Decisionimp 0.90Claim
    -
    Include 3D renders in the standard package — not a paid add-on
    -
    Layer 2A · universal
    -
    🎙 Design Crew Team · ▶ 14:20 · Design Crew Dept
    -
    Design Crew#service-offering#strategy
    -
    Layer 2B · typedsuperseded_by → none · live
    -
    decided_byDesign Crew Team
    -
    rationalelow demand as paid add-on; matches competitors, better client visualization
    -
    -
    -
    Decisionimp 1.00Claim
    -
    Shift to root-cause analysis instead of assigning blame
    -
    Layer 2A · universal
    -
    🎙 Abdelrahman · ▶ 33:11 · After-Sales Dept
    -
    Abdelrahman#root-cause#process-improvement
    -
    Layer 2B · typedsuperseded_by → none · live
    -
    decided_byAbdelrahman
    -
    rationaleblaming delivery doesn't fix the underlying product/process flaw — problems recur
    -
    -
    -
    - - -
    -
    Commitment — reclassified from real tasks; this is the new category
    -
    -
    -
    Commitmentinternal · employee→managerimp 0.95
    -
    Submit a weekly progress report every Thursday
    -
    Layer 2A · universal
    -
    🎙 Abdelrahman → Mina · ▶ 49:33 · After-Sales Dept
    -
    Mina#reporting
    -
    Layer 2B · typedfulfilled_by → this week's report · recurring
    -
    promisorMina (employee)
    -
    promiseeAbdelrahman (manager)
    -
    dueevery Thursday
    -
    deliverableprogress report — needs, cases, fulfilled/unfulfilled
    -
    -
    -
    Commitmentexternal · to clientimp 1.00
    -
    Finalize the Sales Order the moment the client confirms
    -
    Layer 2A · universal
    -
    🎙 Dana Ahmed · ▶ 1:13:27 · Design Crew Dept
    -
    Dana AhmedGuest 2 (client)#order-processing
    -
    Layer 2B · typedfulfilled_by → none yet · open
    -
    promisorDana Ahmed (Ariika)
    -
    promiseethe client (Guest 2)
    -
    dueimmediately on client confirmation
    -
    deliverablefinalized sales order, stock reserved
    -
    -
    -
    - - -
    -
    Task
    -
    -
    -
    Taskimp 1.00pri criticalopen
    -
    Develop SOPs for every role in the after-sales department
    -
    Layer 2A · universal
    -
    🎙 Abdelrahman → Mina · ▶ 40:22 · After-Sales Dept
    -
    Mina#SOPs#operations
    -
    Layer 2B · typedcompleted_by → none · open
    -
    assigneeMina
    -
    deadline— (not stated)
    -
    -
    -
    Taskimp 0.80pri highopen
    -
    Train delivery teams to inspect products on delivery & report issues
    -
    Layer 2A · universal
    -
    🎙 After-Sales · ▶ 51:18 · After-Sales Dept
    -
    #training#quality-control
    -
    Layer 2B · typedcompleted_by → none · open
    -
    assignee— (delivery team lead)
    -
    deadline—
    -
    -
    -
    - - -
    -
    Risk
    -
    -
    -
    Riskscope creepimp 0.80open
    -
    Clients expect architectural work — outside the FF&E service scope
    -
    Layer 2A · universal
    -
    🎙 Design Crew · ▶ 11:00 · Design Crew Dept
    -
    #client-management#scope
    -
    Layer 2B · typedmitigated_by → none · open
    -
    severitymedium
    -
    mitigation3–5 min scope intro at the start of every meeting
    -
    threatens→ commitment "service scope = FF&E only"
    -
    -
    -
    Riskimp 0.90open
    -
    Suppliers aren't committed to delivery timeframes → resolution delays
    -
    Layer 2A · universal
    -
    🎙 After-Sales (re: Khaled) · ▶ 25:43 · After-Sales Dept
    -
    Khaled#supplier-management#procurement
    -
    Layer 2B · typedmitigated_by → none · open
    -
    severityhigh
    -
    mitigationbinding supplier agreements with penalty clauses
    -
    threatens→ the 24h customer-resolution commitment
    -
    -
    -
    - - -
    -
    Note — was "fact"
    -
    -
    -
    Noteimp 0.80
    -
    80% of product issues are supplier defects, not customer misuse
    -
    Layer 2A · universal
    -
    🎙 After-Sales · ▶ 28:04 · After-Sales Dept
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    #quality-control#supplier-management
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    Layer 2B · typedcontradicted_by → none · current
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    value80%
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    contextmajority of issues stem from supplier defects
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    Noteimp 0.90
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    Design tool stack: Co-Home (2D) · Canva (mood) · Gemini (3D)
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    Layer 2A · universal
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    🎙 Design Crew · ▶ 28:50 · Design Crew Dept
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    Co-HomeCanvaGemini#workflow
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    Layer 2B · typedcontradicted_by → none · current
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    valueCo-Home / Canva / Gemini
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    contextestablished, preferred toolchain
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    - Migration from today: - fact + general → note · add commitment + its edge · status stops being a typed box, becomes derived from edges · assigner drops (use entities) · Person / Topic / Speaker are already Layer-2, just leaving the category list. The number stays ~5 — the membership changes. -

    - -
    - - diff --git a/docs/brand/personas/PRODUCT-PERSONAS-UPDATE-2026-06-01.md b/docs/brand/personas/PRODUCT-PERSONAS-UPDATE-2026-06-01.md deleted file mode 100644 index a39a412..0000000 --- a/docs/brand/personas/PRODUCT-PERSONAS-UPDATE-2026-06-01.md +++ /dev/null @@ -1,159 +0,0 @@ -# Knowcap MENA Persona Research — Update 2026-06-01 - -Layer-2 signal validation pass on top of the Phase-1 strategic landscape (see [PRODUCT-PERSONAS.md](./PRODUCT-PERSONAS.md)). This update tests the Phase-1 verdict against **real search-demand and SME-count data** pulled from Google Trends + Apollo.io. - -**TL;DR:** Phase-1 verdict CONFIRMED. The "any SME" hypothesis is still negated. The Odoo-partner beachhead is **quantitatively validated** — Odoo search interest in MENA is 20–50× higher than the entire AI-meeting-tools category combined. Hassan's "MENA Read.ai" thesis is **partially confirmed**: the category is exploding from a near-zero base, meaning the market is forming NOW with nobody winning it yet, BUT search-driven inbound won't work at this scale. Channel must be outbound + founder-led + Odoo-partner referral. - ---- - -## 1. The Odoo beachhead — quantified - -5-year average Google Trends search interest, 0–100 scale, all MENA: - -| Country | Odoo | ChatGPT | "project documentation" | "meeting notes" | -|---|---|---|---|---| -| **Egypt** | **57.2** | 27.5 | 4.0 | 1.7 | -| Morocco | 53.8 | 33.6 | 2.3 | 0.4 | -| UAE | 52.9 | 30.3 | 5.9 | 2.7 | -| Saudi | 49.2 | 28.8 | 5.9 | (error) | -| Lebanon | 42.6 | 32.1 | 0.5 | 0.8 | -| Kuwait | 39.2 | 28.7 | 0.7 | 0.8 | -| Qatar | 34.4 | 22.9 | 1.3 | 0.0 | -| Jordan | 25.8 | 32.1 | 2.2 | 0.4 | - -**Reading the table:** -- **Odoo dominates MENA search.** Egypt is #1 (57.2) — Hassan's home market and where SMEtools sits. Morocco (53.8) and UAE (52.9) are close behind. The Odoo distribution thesis is quantitatively confirmed. -- **ChatGPT interest is meaningful (23–34)** — MENA SMEs are AI-curious. The audience is ready for AI tooling. -- **"Project documentation" and "meeting notes" search interest is near zero (0.4–5.9)** — direct AI-meeting-tool category demand in MENA is essentially nonexistent today. -- Source: Google Trends `interest_over_time`, last 5 years (262 weeks per query). Full data: [trends-mena-interest.csv](./trends-mena-interest.csv) - ---- - -## 2. The "MENA Read.ai" thesis — partially confirmed (with a critical caveat) - -| Country | Rising search query | Growth rate | -|---|---|---| -| Saudi | "ai meeting notes" | **+3,011,100%** | -| Egypt | "read.ai meeting notes" | **+686,750%** | -| UAE | "read.ai meeting notes" | **+418,050%** | -| Egypt | "read ai meeting notes in teams" | +316,250% | -| Saudi | "read.ai meeting notes" | +377,200% | -| UAE | "read.ai meeting notes in teams" | +211,950% | -| UAE | "otter ai" | +130,350% | -| UAE | "fireflies ai" | +126,150% | - -**Reading the data:** -- These are EXPLOSIVE growth rates — the category is being discovered in MENA in real-time. -- BUT the absolute search volume is tiny (0–3 on a 0–100 scale). "Massive percentage growth from a near-zero base." -- Read.ai is the dominant brand MENA users are discovering. Otter.ai and Fireflies are 2× to 3× behind in mindshare. -- Critical caveat: **search-driven inbound marketing won't work** at this scale. The traffic isn't there. The category is forming, but distribution must come from somewhere other than SEO. -- Source: Google Trends `related_queries → rising`, seed term "meeting notes," 8 MENA countries. Full data: [trends-mena-rising.csv](./trends-mena-rising.csv) - ---- - -## 3. Top related queries — what MENA people actually search alongside "meeting notes" - -| Country | #1 related (top relative score 100) | #2 | -|---|---|---| -| UAE | "ai meeting notes" (100) | "meeting notes template" (19) | -| Saudi | "ai meeting notes" (100) | "read.ai meeting notes" (21) | -| Egypt | **"meeting notes template" (100)** | "read.ai meeting notes" (98) | -| Qatar | **"meeting notes template" (100)** | (only result) | - -**Reading the data:** -- **Egypt and Qatar lead with "meeting notes template."** People are still solving the problem with Word/Google Docs templates. This is the EXACT pain Knowcap solves directly — "stop templating your notes, let AI generate them from the recording." -- UAE and Saudi already discover "ai meeting notes" as the primary alternative. They're further along the awareness curve. -- Source: Google Trends `related_queries → top`. Full data: [trends-mena-related.csv](./trends-mena-related.csv) - ---- - -## 4. UAE SME counts per vertical (Apollo, partial pass) - -These are companies with 11-200 employees registered in Apollo with valid contact records. UAE only — KSA/Egypt/Jordan/Kuwait passes failed on Apollo (likely free-trial rate limiting). 6 data points captured before block: - -| Vertical | Apollo count (11–200 employees, UAE) | -|---|---| -| Management consulting | **2,500** | -| Real estate | **2,400** | -| Marketing/advertising | **1,800** | -| Hospitals & health care | **1,000** | -| Accounting | 496 | -| Law practice | 203 | - -**Reading the data:** -- The verticals Hassan cares about (consulting, agencies, real estate) each have 1,800-2,500 SMEs in UAE alone. Market is big enough for a focused vertical play AND a horizontal one. -- Legal (203) is much smaller — but that matches the global pattern (law firms are fewer but pay 5-10× more per seat). -- Source: [MENA-SME-COUNTS.csv](./MENA-SME-COUNTS.csv). The KSA/Egypt/Jordan/Kuwait rows show blank — Apollo's free-trial rate limit hit. To recover: upgrade Apollo to paid tier ($60/mo), OR use LinkedIn Sales Navigator firmographic search (which Hassan is logged into). - ---- - -## 5. Revised verdict: horizontal vs vertical — both, sequenced - -The horizontal-vs-vertical question Hassan asked has a data-backed answer: - -**Vertical first (Odoo partners) — 0 to 100 customers, founder-led** -- Odoo search interest in MENA: 25–57 (massive) -- Founder distribution: 470+ MENA Odoo partners across Egypt (187), Saudi (181), UAE (105) -- Pain: scope creep + manual project documentation (validated by "meeting notes template" being the top related search in Egypt) -- Channel: outbound + founder-led + Odoo community -- Conversion-positioned landing page: knowcap.ai/for/odoo-partners - -**Horizontal awareness in parallel (broad MENA SME) — months 1-12, brand building** -- Category search interest: 0–3 (near zero today) BUT rising 100,000–3,000,000% -- The MENA AI-meeting-notes category is forming. Hassan's "MENA Read.ai" thesis is real — but it's a 12-24 month brand play, not a quick inbound win. -- Channel: founder-led Instagram content (already working — Hassan's Instagram posts are converting), LinkedIn thought leadership, MENA tech press (Wamda, MAGNiTT, Forbes ME) -- Awareness-positioned main page: knowcap.ai = horizontal outcome positioning ("Your meetings become finished work") - -**The 5-vertical sub-page structure recommended:** -1. `/for/odoo-partners` — Phase 1 conversion target (highest match: search demand + distribution + pain) -2. `/for/agencies-and-consulting` — Phase 1 conversion (1,800-2,500 SMEs in UAE alone, scope-creep pain) -3. `/for/real-estate` — Phase 2 (huge MENA segment, 2,400+ in UAE; tilts painkiller in KSA/UAE mega-projects per Phase-1 doc) -4. `/for/audit-and-legal` — Phase 2 conversion (KSA PDPL regulatory pain, fewer firms but $100-500/seat WTP) -5. `/for/healthcare-admin` — Phase 2 (UAE March 2026 AI Act sectoral obligations) - ---- - -## 6. What this changes for the landing page A/B test - -The 4-version A/B test currently live tests **horizontal copy** with thematic variation: -- A: claims → evidence (control) -- B: outcome (meetings become verified actions) -- C: role-first cards (ERP/CRM/Agencies/Teams) -- D: show-the-magic (L1/L2/L3 escalation) - -**Recommendation:** Keep the 4-version test as the horizontal awareness layer. ADD vertical sub-pages over the next 2 weeks targeting: -1. /for/odoo-partners (highest priority — best ROI given search demand + distribution) -2. /for/agencies-and-consulting (second priority — large SME count, validated pain) -3. /for/audit-and-legal (Phase 2 priority — high WTP, regulatory urgency) - -Vertical sub-pages use the **same** design system (impeccable themed-shell) and run paid ads + cold outbound to them. Main horizontal page runs organic + social + brand. - ---- - -## 7. What's still missing / next data passes - -These didn't get fully pulled this session — should run before committing significant ad budget: - -1. **Apollo KSA + Egypt SME counts per vertical** — blocked by free-trial rate limit. Either upgrade Apollo ($60/mo paid) or use LinkedIn Sales Navigator (Hassan logged in) for same data. -2. **Meta Audience Insights** — demographic + interest data for each persona. Hassan is logged into Meta Business Suite. Needs minimum $1 ad spend to unlock Insights. -3. **LinkedIn Sales Navigator firmographic counts** — Hassan is logged in but I haven't driven the searches yet (browser environment got unstable). -4. **YouTube comment mining** — Google API key + YouTube API enabled. Not yet executed; needs ~30 min runtime once browser environment stabilizes. Drops Reddit equivalent for MENA. -5. **Customer conversations (irreplaceable)** — talk to 10-15 of the Instagram-warm contacts. Persona research from secondary sources confirms patterns; conversion comes from real human interest. This is the most valuable next action even though it can't be automated. - ---- - -## Data files in this folder - -- [trends-mena-interest.csv](./trends-mena-interest.csv) — 102 rows, search interest per country/query (5y avg) -- [trends-mena-rising.csv](./trends-mena-rising.csv) — 14 rows, breakout queries per country -- [trends-mena-related.csv](./trends-mena-related.csv) — 19 rows, top related queries per country -- [MENA-SME-COUNTS.csv](./MENA-SME-COUNTS.csv) — partial Apollo data (6 UAE rows valid; KSA/EG blocked) -- [PRODUCT-PERSONAS.md](./PRODUCT-PERSONAS.md) — Phase 1 strategic landscape (14 segments) - ---- - -## Bottom line for Hassan - -Your "any SME" instinct from Instagram interest **is real but uneven**. The market IS forming across MENA SMEs (rising-search data proves this). But the demand is too small TODAY to drive inbound — and Odoo (your distribution moat) is 20-50× more searched than the AI-meeting-tools category combined. **Sequence wins this:** Odoo partners → consulting/agencies → regulated. The Instagram warmth is the awareness layer; vertical conversion is where the first $100K of revenue comes from. - -Run the conversations with the 10-15 Instagram-warm contacts before you build 5 sub-pages. That's the only data point that will tell you if a non-Odoo SME will actually PAY (not just say "interesting"). diff --git a/docs/brand/personas/PRODUCT-PERSONAS.md b/docs/brand/personas/PRODUCT-PERSONAS.md deleted file mode 100644 index 4e5f9c6..0000000 --- a/docs/brand/personas/PRODUCT-PERSONAS.md +++ /dev/null @@ -1,210 +0,0 @@ -# Knowcap MENA SME Segmentation Landscape - -**Research question:** Across MENA SMEs (10–200 employees), which segments face the strongest pain around "AI agents acting on unverified information from meetings, calls, and chats"? Does the "any SME" hypothesis hold, or does the documented beachhead (Odoo partners + regulated verticals) survive scrutiny? - -**Date:** 2026-06-01 -**Method:** Adversarial 3-vote verification of 25 source-grounded claims; 7 survived (3 high-confidence regulatory, 4 framing/market signals). - ---- - -## Executive summary - -The "any SME" hypothesis is **negated.** The MENA-side evidence that survived adversarial verification points in one direction: the buyers who feel acute, regulator-induced pain around "AI agents acting on unverified information" are concentrated in **Saudi Arabia under PDPL enforcement** (48 SDAIA decisions in 12 months, SAR 5M fines, no SME exemption — Clyde & Co Mar 2026, IAPP, Morgan Lewis, DLA Piper) and in **UAE financial services / e-commerce / edtech / health under sectoral AI obligations** (Latham & Watkins Oct 2025, CBUAE Feb 2026 guidance, UAE PDPL). General "MENA tech press" frames AI trust as "ethical design + human oversight" but does NOT yet articulate the specific verification-before-action pain Knowcap solves (Wamda Sept 2025), meaning awareness-led inbound is weak — outbound and partner-channel is required. The documented Knowcap beachhead — **Odoo implementation partners + regulated verticals (finance, legal, health)** — is the correct Phase 1/2, and we should ADD UAE edtech/digital platforms (sectoral Tier-3 risk classification, March 2026 effective). Marketing/sales/ops productivity SMEs remain anti-buyers (Granola/Fathom territory; no regulator driving spend; commoditised). Net: confirm beachhead, expand Phase 2 to include edtech/digital platforms, refuse "any SME" framing. - ---- - -## Landscape map: 14 candidate segments - -Rated on: **Pain** (painkiller / vitamin / red ocean), **Reachability in MENA**, **WTP**, **Buyer persona**, **Arabic/RTL need**, **AI adoption**, **Distribution channel**. - -### 1. Odoo implementation partners — **PAINKILLER (CONFIRMED BEACHHEAD)** - -- **Pain event:** Mid-project requirements drift kills margins. PM realises in week 8 that the client's "we already agreed in the kickoff call" doesn't match what's in Odoo Studio. Without a verified record of what was decided in which meeting, the partner eats the scope change or loses the client. (Note: the specific "ERP implementation failure stats" claim from godlan.com was **refuted 0-3** in adversarial verification — we have NO verified third-party stat on ERP scope-creep cost. Pain is real per founder's Odoo-partner insider knowledge but not externally substantiated.) -- **Reachability MENA:** Odoo Partner Portal (470+ MENA partners; Egypt 187, Saudi 181, UAE 105 per founder's known distribution); Odoo Experience Dubai annual; Odoo Community Days; Odoo Functional Consultant LinkedIn Group; partner-channel WhatsApp groups (private, founder has access via SMEtools). -- **WTP:** $30-60/seat/month. Reference: they sell their own consulting at $50-150/hr and pay $20-40/seat for Odoo.sh + ~$10/seat for Notion/ClickUp. -- **Buyer:** Implementation Project Manager / مدير مشروع التطبيق. Trigger: 2nd or 3rd scope-creep loss in a quarter. Stack: Odoo + WhatsApp Business + Gmail + Notion/ClickUp. Block: "we already use meeting notes in Notion" — reframe as audit trail, not notes. -- **Arabic:** English UI fine for the PM tier; client-facing artefacts (SOW deltas, decision logs) need Arabic export for KSA/Egypt clients. -- **AI adoption:** High. Already using ChatGPT for SOW drafting, Claude for Odoo Python customisations. -- **Channel:** Founder-led sales via SMEtools network → partner-channel (revenue share with Odoo partners selling Knowcap to their downstream clients). - -### 2. Marketing/creative agencies — **VITAMIN (AVOID)** - -- **Pain event:** None forced by regulator. Agencies already over-served by Otter, Fathom, Granola, Fireflies. Account managers want better recall, not verified-before-action. -- **Reachability:** Step Conference Dubai, RiseUp Summit Cairo, IAB MENA, Dubai Lynx, MENA Effie Awards, Campaign Middle East — but presence here means red-ocean competition. -- **WTP:** $15-25/seat/month, ceiling at Fathom/Granola pricing. -- **Buyer:** Account Director / مدير حساب. Trigger: nothing forced; nice-to-have. -- **Arabic:** Need bilingual transcripts (creative briefs are bilingual). -- **AI adoption:** High but saturated tooling. -- **Channel:** None viable — refer them to Granola/Fathom per existing strategy. -- **Verdict:** Anti-buyer. - -### 3. Boutique strategy/ops consulting firms — **PAINKILLER (Phase 2)** - -- **Pain event:** Recommendation traceability. A partner makes a recommendation to a Saudi/Emirati client board; 6 months later board asks "where did this number come from?" Without verified meeting → claim → confirmed-by-named-human chain, the partner is exposed. -- **Reachability:** Strategy& Middle East alumni network; INSEAD MENA Council; Harvard Business School MENA Club; Wamda Pro; consulting LinkedIn groups; smaller firms reachable via LinkedIn outbound to Partner/Director titles. -- **WTP:** $80-150/seat/month. Partners bill $300-800/hr; tooling spend per seat is small change. -- **Buyer:** Engagement Manager → Partner / شريك or مدير ارتباط. Trigger: board challenge on a past recommendation; first wave of AI-generated decks creating provenance anxiety. -- **Arabic:** English-first; Arabic exports for client-facing deliverables only. -- **AI adoption:** Very high (ChatGPT Enterprise, Claude, custom GPTs for benchmarking). -- **Channel:** Founder-led sales + Partner LinkedIn outbound + Strategy& alumni warm-intro. - -### 4. Audit / accounting firms (Big 4 satellites + local mid-market) — **PAINKILLER (Phase 2, KSA-first)** - -- **Pain event:** Saudi PDPL Article 36 — up to SAR 5M/violation, doubled for repeat (verified 3-0 by Clyde & Co, A&O Shearman, CMS Law, IAPP, Baker McKenzie, DLA Piper). 48 SDAIA enforcement decisions in 12 months. Audit firms handle KSA client PII; an AI agent auto-drafting an engagement letter or audit memo from an unverified transcript of "what the CFO said" is a direct PDPL Article 35/36 exposure. -- **Reachability:** Saudi Organization for Chartered and Professional Accountants (SOCPA); UAE Accountants and Auditors Association; ACCA MENA; ICAEW Middle East; LinkedIn (Senior Audit Manager / Partner titles). -- **WTP:** $60-120/seat/month. Comparable to their per-seat spend on Caseware, MindBridge, Validis. -- **Buyer:** Audit Partner / شريك مراجعة + Risk & Compliance Director. Trigger: SDAIA enforcement decision against a peer firm; client RFP requires AI governance attestation. -- **Arabic:** Bilingual mandatory for KSA client work. -- **AI adoption:** Moderate-high; cautious. Big 4 have AI policies; mid-market firms experimenting. -- **Channel:** Founder-led + KSA-focused content (PDPL-compliant AI Q&A playbook) + SOCPA partnership. - -### 5. Law firms (regulatory / M&A / real estate) — **PAINKILLER (Phase 2, KSA + UAE)** - -- **Pain event:** ABA Opinion 512 analog pressure + KSA PDPL on client data + UAE PDPL deadline 1 Jan 2027 (Latham, Bird & Bird, CMS Jan 2026). A partner reviewing an AI-drafted memo for a multi-million-dirham real estate transaction needs verified provenance per claim. -- **Reachability:** International Bar Association MENA; UAE Federal Authority for Identity, Citizenship, Customs & Port Security partner programs; Saudi Bar Association; ALB Middle East; Lexis Middle East Law Awards; LinkedIn outbound. -- **WTP:** $100-200/seat/month (matches NetDocuments, iManage seat pricing). -- **Buyer:** Managing Partner / المحامي الرئيسي + KM/Innovation Director. Trigger: hallucination incident in a peer firm + PDPL enforcement headline. -- **Arabic:** Arabic non-negotiable for KSA practice; English-only acceptable for UAE international-firm satellites. -- **AI adoption:** Moderate. Harvey AI, Spellbook entering market; conservative partners still cautious. -- **Channel:** Founder-led + IBA MENA content sponsorship + KSA Bar Association partnership. - -### 6. Real estate brokerages and developers — **VITAMIN tilting PAINKILLER in KSA/UAE mega-projects** - -- **Pain event:** Off-plan sales disputes; broker promises in WhatsApp later contradicted. PDPL applies if processing buyer PII via AI. Not yet a top-of-mind pain. -- **Reachability:** Cityscape Global Riyadh + Dubai; Arabian Business Real Estate; Dubai Land Department partner network; RERA Saudi; LinkedIn (Sales Director titles). -- **WTP:** $25-50/seat/month. Adjacent tools: Bayut/Property Finder Pro, Bitrix24, Zoho CRM. -- **Buyer:** Head of Sales / مدير المبيعات. Trigger: legal exposure from buyer dispute citing WhatsApp/call promises. -- **Arabic:** Arabic essential — buyer comms are predominantly Arabic. -- **AI adoption:** Low-moderate; CRM-driven, ChatGPT for listings. -- **Channel:** Defer to Phase 3. - -### 7. Healthcare administration (polyclinics, dental chains, medical groups) — **PAINKILLER (Phase 2)** - -- **Pain event:** UAE explicitly classifies "medical diagnostics" as Tier 3 high-risk under March 2026 AI Act framework (verified 2-1 with corroboration from Latham, Pinsent Masons, 6clicks, digitaldubai.ai). KSA PDPL applies to patient data with no SME exemption. An admin AI agent auto-confirming a procedure based on an unverified call transcript = direct exposure. -- **Reachability:** Arab Health Dubai (Jan annual); Saudi Health Conference; Egypt Healthcare Conference; HIMSS Middle East; Dubai Health Authority partner programs; MENA Healthcare Investment Conference. -- **WTP:** $40-80/seat/month for admin tier; not clinical. -- **Buyer:** Operations Director / مدير العمليات + Quality & Compliance Manager. Trigger: DHA/MOH compliance audit; AI Act self-assessment deadline Sept 2026 (UAE). -- **Arabic:** Bilingual mandatory. -- **AI adoption:** Low-moderate; admin still spreadsheet-heavy; clinical workflow tools dominate. -- **Channel:** Arab Health booth + DHA partnership + content on PDPL + AI Act for healthcare admins. - -### 8. Software/SaaS development shops + IT consulting — **VITAMIN (mostly)** - -- **Pain event:** Spec-vs-built drift, similar to Odoo partners but without the same regulatory shield. They're already heavy AI users and skeptical of meta-tooling. -- **Reachability:** RiseUp Summit Cairo, Step Dubai, GITEX, MENA Devs LinkedIn, Itana, Flat6Labs alumni. -- **WTP:** $20-40/seat/month. -- **Buyer:** Engineering Manager / Tech Lead. Trigger: post-mortem on a missed-spec project. Weak signal. -- **Arabic:** English-only fine. -- **AI adoption:** Very high. -- **Channel:** Content/SEO + dev communities. Not a Phase 1 priority. -- **Verdict:** Lukewarm. Possible Phase 3 if Odoo-partner play extends to "any implementation services firm." - -### 9. Architecture & engineering firms — **VITAMIN** - -- **Pain event:** Design-decision traceability on mega-projects (NEOM, Red Sea, Diriyah, UAE infrastructure). Real but slow-moving buying cycle. -- **Reachability:** Big 5 Construct Saudi + UAE; MENA FM; Saudi Council of Engineers; UAE Society of Engineers; Construction Week MENA. -- **WTP:** $50-100/seat/month. -- **Buyer:** Project Director / مدير المشروع. Trigger: claim/variation dispute on a giga-project. -- **Arabic:** Bilingual. -- **AI adoption:** Low-moderate (BIM-focused). -- **Channel:** Phase 3. - -### 10. Trading and import-export — **RED OCEAN / NO FIT** - -- **Pain event:** None clear. WhatsApp-based deal flow; AI not yet meaningful in workflows. -- **Verdict:** Skip. - -### 11. F&B chains / hospitality groups — **RED OCEAN / NO FIT** - -- **Pain event:** None for verification thesis. POS-driven operations. -- **Verdict:** Skip. - -### 12. Family-owned holding companies (the "diwan" mid-market) — **VITAMIN (PERSONAL-OS LAYER ONLY)** - -- **Pain event:** Family principal wants their AI assistant to be trustworthy across investments, real estate, philanthropic boards. This is Knowcap Layer 3 (personal-OS), not Layer 1/2. -- **Reachability:** Family Business Network MENA; Tharawat Family Business Forum; Dubai International Financial Centre (DIFC) family wealth programs. -- **WTP:** $200-500/seat/month — but tiny seat count (1-5 per family). -- **Buyer:** Chief of Staff to the Principal. Trigger: AI hallucination embarrassment. -- **Arabic:** Bilingual. -- **AI adoption:** High at the principal level; chief-of-staff already running custom GPTs. -- **Channel:** Warm intro only; not scalable. -- **Verdict:** Opportunistic, not segmental. - -### 13. Manufacturing SMEs — **NO FIT** - -- **Pain event:** None for verification thesis. Floor operations don't generate "claims for agents to act on." -- **Verdict:** Skip. - -### 14. Logistics/freight forwarders — **NO FIT** - -- **Pain event:** None. WMS/TMS-driven, document-flow not claim-flow. -- **Verdict:** Skip. - -### ADD-15. UAE Edtech + digital platforms — **PAINKILLER (Phase 2 ADDITION)** - -- **Pain event:** UAE Federal Decree-Law No. 26 of 2025 (Child Digital Safety) + March 2026 AI Act Tier-3 classification for "education and health AI platforms" with **child-safe design integration mandatory** (Latham Oct 2025, uaeahead Jan 2026, digitaldubai.ai). An AI tutoring agent that acts on unverified parent/teacher communications = direct child-data-protection exposure. -- **Reachability:** GESS Dubai; Bett MEA; ASU+GSV MENA; Edtech Arabia; ADEK / KHDA partner programs. -- **WTP:** $40-80/seat/month. -- **Buyer:** Head of Product / Chief Compliance Officer. Trigger: AI Act self-assessment deadline Sept 2026. -- **Arabic:** Bilingual mandatory. -- **AI adoption:** High for product, moderate for governance. -- **Channel:** GESS booth + Latham/Bird & Bird co-content + KHDA partnership. - -### ADD-16. UAE Financial services (regulated SME tier — fintech, payment platforms, small asset managers) — **PAINKILLER (Phase 2 ADDITION)** - -- **Pain event:** UAE Financial Services classified by Latham (Oct 2025) and uaeahead (Jan 2026) as the most-AI-regulated sector: "credit scoring, AML, robo-advisory, algorithmic trading must be assessed against prudential, conduct, governance, operational resilience obligations." CBUAE Guidance Note on AI (Feb 2026) recommends human-in-the-loop / human-on-the-loop (non-binding but de facto pressure). -- **Reachability:** DIFC Innovation Hub; ADGM RegLab; MENA Fintech Association; Fintech Surge Dubai; Seamless Saudi Arabia. -- **WTP:** $100-200/seat/month (matches OneTrust, Persona seat pricing for compliance tools). -- **Buyer:** Chief Compliance Officer + MLRO. Trigger: CBUAE thematic review; ADGM/DIFC license renewal. -- **Arabic:** English-first; Arabic for MoF / SCA submissions. -- **AI adoption:** High; already using Persona, ComplyAdvantage, Chainalysis. -- **Channel:** DIFC/ADGM partnership + founder-led + MENA Fintech Assoc. - ---- - -## Top 3 MENA segments to target first - -### 1. Odoo implementation partners (Egypt / KSA / UAE — 470+ partners) -- **Pain event triggering purchase:** 2nd quarterly scope-creep loss; client dispute "we said X in the kickoff call." -- **Channel:** Founder-led via SMEtools network → Odoo Partner Portal outbound → partner-channel revenue share. -- **First 10 named prospects:** Not in surviving evidence — founder's insider list required (SMEtools CRM holds canonical roster). - -### 2. KSA audit / accounting / law firms under PDPL exposure -- **Pain event:** Peer firm SDAIA enforcement decision (48 already issued — Clyde & Co Mar 2026, IAPP); client RFP requires AI governance attestation; SAR 5M fine risk. -- **Channel:** SOCPA + Saudi Bar Association partnerships, KSA-content marketing on "PDPL-compliant AI workflows," LinkedIn outbound to Audit Partner + Risk Director. -- **First 10 named prospects:** Specific firm list not in surviving evidence; SDAIA's 48 published decisions provide the universe to mine via IAPP and Alnafitha's enforcement breakdowns. - -### 3. UAE financial services + edtech/digital platforms under March 2026 AI Act sectoral obligations -- **Pain event:** UAE AI Act self-assessment deadline Sept 2026 (Latham, digitaldubai.ai); CBUAE Feb 2026 guidance creates de facto human-oversight pressure; Tier-3 high-risk classification for credit scoring / medical diagnostics / hiring / education. -- **Channel:** DIFC / ADGM / KHDA partnerships; MENA Fintech Association; Latham co-content on UAE AI Act compliance playbook. -- **First 10 named prospects:** Not in surviving evidence; DIFC Innovation Hub + ADGM RegLab cohorts are the named lead lists. - ---- - -## 3 segments to EXPLICITLY avoid - -1. **Marketing / creative agencies** — saturated by Granola/Fathom/Otter; no regulator forcing spend; the exact "pure productivity workflow" anti-buyer the existing strategy doc names. -2. **Trading / import-export + F&B / hospitality + Manufacturing + Logistics** — no verification pain, WhatsApp-driven deal flow or POS-driven ops, no AI-agent surface area, no MENA precedent for buying "trust layer" tooling. -3. **Software / SaaS dev shops as a primary segment** — high AI literacy means high skepticism of meta-tooling; the Odoo-partner pain doesn't transfer cleanly because they have less regulatory shield. Possible Phase 3, not Phase 1. - ---- - -## Biggest gap in the data before committing budget - -**The MENA-side conversion evidence is missing.** Surviving claims confirm: (a) regulatory pressure is real in KSA (PDPL Article 36 / 48 SDAIA decisions / SAR 5M fines) and UAE (sectoral AI obligations, March 2026 AI Act); (b) mainstream MENA tech press doesn't yet frame the verification pain in Knowcap's terms (Wamda Sept 2025). What we do NOT have verified third-party evidence for: - -- **ERP scope-creep / implementation-failure stats** — the godlan.com claims were refuted 0-3. The Odoo-partner pain is founder-known but externally unsubstantiated. We need 5-10 MENA Odoo-partner interviews to confirm scope-creep cost per project. -- **MENA AI adoption percentages** — every adoption-rate claim (39% enterprise GenAI, 75% MEA employee AI use, 32% daily use, 84% CEO readiness, 48% data-privacy barrier) was refuted 0-3 to 1-2. The IBM and GSMA secondary sources couldn't survive verification. -- **Named-prospect lists** — none of the surviving claims provide first-10 prospects per segment. SMEtools CRM + DIFC/ADGM/SOCPA roster mining required before outbound budget commits. -- **WTP benchmarks** — adjacency pricing in the report is reasoning-from-known-tools, not surveyed MENA willingness-to-pay. Need 10-20 buyer interviews before pricing locks. - ---- - -## Verdict on "any SME" hypothesis - -**NEGATED.** The adversarial-verified evidence supports the documented beachhead exactly: -- **Phase 1 painkiller:** Odoo implementation partners (founder distribution + scope-creep pain). -- **Phase 2 painkiller:** Regulated verticals — KSA-anchored (PDPL Article 36, SDAIA enforcement) + UAE-anchored (sectoral AI obligations for finance / edtech / health / digital platforms). -- **Anti-buyer:** Marketing / sales / pure-productivity SMEs (Granola/Fathom commoditised). - -The only adjustment to existing strategy: **add UAE edtech + digital platforms to Phase 2** alongside finance / legal / health, because UAE's March 2026 AI Act Tier-3 classification + Child Digital Safety Law + CBUAE Feb 2026 guidance create the same regulator-forced verification pain in those sectors. diff --git a/docs/brand/screenshots/README.md b/docs/brand/screenshots/README.md deleted file mode 100644 index 75a8c6d..0000000 --- a/docs/brand/screenshots/README.md +++ /dev/null @@ -1,82 +0,0 @@ -# Knowcap product screenshot library - -Curated screenshots of the Knowcap product surfaces, used by the [`blogger`](../../../routines/blogger/) routine (and any future blog or comparison-page routine) to embed visuals in posts. - -## Scope vs. other repos - -This folder holds **product UI captures** (the actual Knowcap app at app.knowcap.ai / hassan.knowcap.ai). It does NOT hold: -- Brand identity assets (logo, type, color swatches) — those live in `../` (the broader `docs/brand/` folder) -- Generative imagery (Higgsfield photoreal, Hyperframes motion graphics) — those live in [`knowcap-content/brand/`](https://github.com/Knowcap-V2/knowcap-content/tree/main/brand) - -If you're wondering "which repo gets this asset?": -- Photo of UI shipped to customers → here -- AI-generated photo of a person using Knowcap → `knowcap-content/` -- Logo PNG → `docs/brand/` (parent folder, not this one) - -## Layout - -``` -docs/brand/screenshots/ -├── README.md ← this file -├── _index.json ← machine-readable index (used by blogger routine) -├── / -│ ├── full.png ← 1600×900 (or aspect-matched) hero capture -│ ├── thumb.png ← 800×450 inline-blog crop -│ └── meta.yaml ← alt text, captions, what it proves, personas it serves -└── _archive/ ← old captures dated and kept for backfill -``` - -## meta.yaml shape - -```yaml -slug: verification-inbox -title: "Inbox after a meeting — claims extracted, not confirmed" -alt: "Knowcap inbox showing 12 extracted claims from a 47-minute meeting, each in pending state with confirm/reject buttons" -caption: "Every meeting produces claims. None of them act until a named human confirms." -captured_date: 2026-06-02 -captured_from: hassan.knowcap.ai # or app.knowcap.ai -surface: "/inbox?source=" -what_it_proves: - - extraction works automatically - - verification step is explicit - - no-confirm-all-button rule visible -personas: [odoo-partners, mena-audit-firms, mena-agencies, regulated-verticals] -features: [verification, inbox, pending-claims] -# Optional -notes: "Use 1600x900 crop, the right rail can be cut off for blog use" -``` - -## Refresh cadence - -Library drifts when the UI changes. Maintenance: - -- **Quarterly:** sweep through `_index.json`, recapture any surface that's visibly changed in the live app -- **Per-feature ship:** when a major new surface ships (new page, redesigned modal), capture it during the same week and update `_index.json` -- **Automated drift detection (future):** a `screenshot-drift-audit` routine compares live captures against library hashes monthly, opens a PR with diffs - -## How the blogger routine uses this - -1. After generating the draft, scan body for trigger keywords (inbox, confirm, audit trail, Odoo, etc.) -2. Match against `_index.json` → filter by features + persona -3. Pick up to 4 best matches -4. Embed as markdown image tags at end of relevant section, using `alt` + `caption` from meta.yaml - -See [`../../../routines/_skills/write-blog-draft/SKILL.md`](../../../routines/_skills/write-blog-draft/SKILL.md) for the full trigger map. - -## Capture standards (when adding new screenshots) - -- **Resolution:** full = 1600x900 (16:9) or 1400x900 (3:2). Thumb = 800x450. -- **Browser chrome:** crop out the browser address bar — show only the app -- **PII:** mask emails, real names, real org/project names — use generic placeholders for production captures -- **Anti-pattern:** no Loom-style cursor highlight rings (looks dated, sales-y). Plain screenshots only. -- **State setup:** capture meaningful state — an empty inbox is a bad capture; an inbox with 8-12 pending claims is good -- **Format:** PNG (lossless), not JPG. File size ~200-400KB per full capture is fine. - -## Adding a new screenshot — checklist - -1. Capture in browser at 1600x900 viewport (use DevTools device toolbar for exact size) -2. Save as `docs/brand/screenshots//full.png` -3. Create `docs/brand/screenshots//thumb.png` (downscale to 800x450) -4. Write `docs/brand/screenshots//meta.yaml` (see shape above) -5. Run `routines/_skills/audit-seo/regenerate-screenshot-index.sh` to update `_index.json` (or do it manually for now — script TBD) -6. Commit; the next routine run can use it diff --git a/docs/brand/screenshots/_index.json b/docs/brand/screenshots/_index.json deleted file mode 100644 index ae9ddff..0000000 --- a/docs/brand/screenshots/_index.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "$schema": "./_index.schema.json", - "version": 1, - "last_updated": "2026-06-02", - "screenshots": [], - "_notes": [ - "Empty until initial capture pass completes (see capture-plan.md)", - "Routines read this file at runtime to know what's available", - "Each entry mirrors the meta.yaml of its / folder — keep in sync", - "Future: a regenerate-index.sh script will rebuild from meta.yaml files" - ] -} diff --git a/docs/brand/screenshots/capture-plan.md b/docs/brand/screenshots/capture-plan.md deleted file mode 100644 index fe32fa1..0000000 --- a/docs/brand/screenshots/capture-plan.md +++ /dev/null @@ -1,78 +0,0 @@ -# Initial capture plan — screenshot library v0 - -Target: ~25 surfaces covering the load-bearing visuals for the 4 ICPs and the verification thesis. - -## Capture priority (tiered) - -### Tier 1 — used in nearly every blog (capture first) - -| Slug | Surface | Why | -|---|---|---| -| `verification-inbox-pending` | Inbox with extracted-but-unconfirmed claims (8-12) | The "extraction is automatic, action is not" thesis | -| `claim-confirmation-step` | One claim being confirmed (confirm/reject UI visible) | The named-human gate | -| `source-page-verified` | Source page with verified tags, speaker attribution, timestamps | The audit-trail/provenance proof | -| `memory-categories` | Memory list filtered by category (decisions/risks/tasks/facts) | The 4-category extraction model | -| `no-confirm-all-rule` | The settings/UX area where "Confirm All" would be — and isn't | The locked design rule | - -### Tier 2 — used in 50%+ of blogs - -| Slug | Surface | Why | -|---|---|---| -| `routine-list` | Routine library view | "Routines act on confirmed facts" | -| `routine-edit` | Single routine config | Routine→Skill→Run model in product | -| `skill-library` | Skills page | The WHAT layer | -| `memory-search-by-speaker` | Memory search filtered by named human | Provenance lookup | -| `agent-action-pr` | An agent's PR to GitHub or ticket to Odoo (the "draft to inbox" pattern) | Action with audit | -| `org-instructions-page` | Organization-level instructions UI | Multi-tier instructions hierarchy | -| `connection-list` | Integrations / connections page | Where Odoo, GitHub, etc. live | - -### Tier 3 — persona-specific - -| Slug | Surface | Persona | -|---|---|---| -| `odoo-multi-instance-connection` | Odoo connection setup, multi-instance | Odoo partners | -| `odoo-routine-push` | A routine pushing a confirmed task to Odoo | Odoo partners | -| `audit-trail-export` | Audit trail download UI (for compliance) | MENA audit firms | -| `pdpl-compliance-section` | Settings page showing data retention/regional storage controls | MENA audit firms (PDPL Art 36) | -| `multilingual-mid-meeting` | Source page showing language-switched segments (English↔Arabic mid-call) | MENA agencies | -| `shared-meeting-cross-org` | Shared-meeting flow showing first-confirmer-wins | Agencies + multi-org founders | -| `project-instructions-page` | Project-level instructions UI | Multi-tenant founders | - -### Tier 4 — supplementary - -| Slug | Surface | Why | -|---|---|---| -| `live-recording-screen` | The recording-in-progress UI | Onboarding visual | -| `upload-source-screen` | Drag-drop file upload (for blogs about retroactive ingestion) | Onboarding visual | -| `home-dashboard-light` | Default home view, light theme | Hero visual | -| `home-dashboard-dark` | Same in dark theme | Hero visual variant | -| `chat-with-citations` | A chat answer with timestamp citations clickable | "Search vs. cite" demo | - -## Capture method - -1. Use real Chromium via `connect-chrome` (gstack browser) on port 34567 or fresh port -2. Sign Hassan in once at start of session -3. Set viewport to 1600x900 via DevTools device toolbar -4. For each Tier 1+2 surface: - - Navigate to the surface - - Set up meaningful state (e.g., for verification-inbox: make sure 8-12 pending claims exist; if not, run extraction on a recent source first) - - Capture full-page screenshot to a file - - Note any masking needed (real names, real emails) -5. Save to `docs/brand/screenshots//full.png` -6. Downscale to thumb.png (800x450) via `sharp` or manual crop -7. Write meta.yaml - -## Estimated time - -- Tier 1 (5 surfaces): 30 min — these need state setup -- Tier 2 (7 surfaces): 30 min — most should be ready-state -- Tier 3 (7 surfaces): 45 min — persona-specific state setup, some may need product work to demonstrate (e.g., Odoo multi-instance might not exist yet — defer) -- Tier 4 (5 surfaces): 15 min — quick captures - -Total: ~2 hours for full library, ~30 min for Tier 1 alone. - -## What's deferred - -- Animated captures (Loom-style) — out of scope; static only -- Multi-step flow captures (sequence of screens) — capture each step as its own slug, link in caption -- Mobile viewport captures — defer until first mobile-focused blog diff --git a/docs/campaigns/landing-pages/education-first-decision.md b/docs/campaigns/landing-pages/education-first-decision.md deleted file mode 100644 index 68b88a2..0000000 --- a/docs/campaigns/landing-pages/education-first-decision.md +++ /dev/null @@ -1,28 +0,0 @@ -# Education-First Landing Page - -**Decision date:** Feb 2026 -**Stakeholders:** Hassan, Omar, Ismail, Ziad - -## The Decision - -| Approach | Why considered | Result | -|---|---|---| -| **Education-first** (Loom-style) | Teach user what product does before signup | **Chosen** — Knowcap is a new category, prospects don't know what to expect | -| **Product-led** (Lovable.com style) | No landing page, just product UX | Rejected for launch — too much cognitive load for category-creation phase | - -## Page Layout -- **Sources panel** (left) + **Studio/workspace panel** (right) — mirrors product UI -- Animated transitions between panels -- **Interactive icons** for the five elements (Governance / Agents / Artifacts / Memory / Intelligence) — each icon triggers a micro-demo animation -- One generic LP first; segment-specific variants after 4–6 weeks of paid data - -## Content Hierarchy -1. Hero — what Knowcap does in one sentence -2. The 5 elements (interactive icon strip with micro-animations) -3. Demo video (or animated event video) -4. Pricing tiers -5. Free trial signup - -## Source notes -- `vibe/llm-wiki/wiki/Knowcap/decisions/2026-02-12 - Education-first landing page approach for launch.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2026-02-12 - Landing Page Design Strategy Discussion.md` diff --git a/docs/campaigns/linkedin-outbound.md b/docs/campaigns/linkedin-outbound.md deleted file mode 100644 index 0781469..0000000 --- a/docs/campaigns/linkedin-outbound.md +++ /dev/null @@ -1,33 +0,0 @@ -# LinkedIn Outbound Campaign - -**Partner:** Ibrahim (Iraq-based LinkedIn specialist) / Kim (Heyreach + Sales Navigator setup) -**Discussed:** Oct 2025 -**Status:** Pricing confirmed, not yet launched - -## Mechanics -- **List building:** LinkedIn Sales Navigator filtered by job title, company size 11–200, industry -- **Automation:** Heyreach (or similar) for multi-account outbound -- **Volume:** ~1,500 messages/month per account; 3 accounts = 4,500/month -- **Expected results:** 8–15 booked calls per account/month → minimum 20–25 calls/month total - -## Messaging Approach -**Non-salesy product-feedback framing:** -> "I'd love some product feedback on how your team would use this." - -Leads to demo → leads to purchase. NOT "here's what I do, do you want to buy?" - -## Pricing Models -| Model | Cost | -|---|---| -| Retainer (2 accounts) | $3,000/mo (50% discount until 10 qualified leads) | -| Retainer (3 accounts) | $4,000/mo (same discount terms) | -| Pay-per-lead | $750 setup + $250 / qualified lead | -| Tool-only (2 accts) | $1,500/mo | -| Tool-only (3 accts) | $2,000/mo | - -## Test Matrix -3 industries × 3 messages each = 9 combinations running simultaneously. Quick signal on what converts. - -## Source notes -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2026-02-12 - Ibrahim Linkedin Outbout Iraq.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Third Parties/2025-10-08 - Hassan x Kim Linkedin navigator.md` diff --git a/docs/campaigns/meta-paid-sprint.md b/docs/campaigns/meta-paid-sprint.md deleted file mode 100644 index adc1884..0000000 --- a/docs/campaigns/meta-paid-sprint.md +++ /dev/null @@ -1,39 +0,0 @@ -# Meta 90-Day Paid Sprint - -**Agency:** StratDev (Freddie Francis CEO; Mike — media buyer, ~$500M lifetime spend; Andres — design; Matt — CS) -**Engagement:** Oct 2025 kickoff; Feb 2026 follow-ups; target launch Dec 2025 / Jan 2026 -**Status:** Active - -## Why Meta over Google -Knowcap is a new category — no existing search demand. Meta builds awareness; Google would only capture demand that doesn't yet exist. Mike (StratDev) recommended Meta-first. - -## Sprint Structure -- **3–4 audience segments** running simultaneously (see [`../brand/legacy/icp-segments-oct2025-stratdev.md`](../brand/legacy/icp-segments-oct2025-stratdev.md)) -- **10+ creative angles per segment** — governance, team audit, remote team mgmt, SOP gen, sales monitoring -- **Daily spend:** $150–200 -- **CAC target:** under $50 per free trial signup -- **Outcome:** identify converting audience + winning message → expand to Google + LinkedIn retargeting - -## Pricing -| Item | Cost | -|---|---| -| Setup (month 1) | $3,250 (LP design $1,750 + ad setup $1,500 — discounted from $4,000 because Hassan has in-house dev) | -| Monthly mgmt | $2,000/mo (for spend under $13,334/mo) | -| Above $13.3K/mo spend | 15% of spend | -| Min ad spend | $2,000/mo | - -## Landing Page Approach -- Start with **one generic LP** — explains product, shows pricing tiers, converts to free trial -- After 4–6 weeks of data: build segment-specific LPs for top performers -- Conversion benchmark: 4%+ on dedicated LP vs 2% on homepage -- StratDev designs; Hassan's dev implements (cost saving) - -## Creative Production -- Repurpose existing 60-second demo video as ad creative base -- Animated event video (see [`../content-pipeline/video/event-animated-video.md`](../content-pipeline/video/event-animated-video.md)) can be cut into ad-length variants -- Five-element framework (Governance / Agents / Artifacts / Memory / Intelligence) provides creative structure - -## Source notes -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2025-10-20 - Knowcap x StartDev.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2025-10-27 - Stardev Kickoff Meeting.md` -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2026-02-12 - Stardev x Knowcap.md` (and variants) diff --git a/docs/campaigns/stratdev/README.md b/docs/campaigns/stratdev/README.md deleted file mode 100644 index d5d209f..0000000 --- a/docs/campaigns/stratdev/README.md +++ /dev/null @@ -1,68 +0,0 @@ -# StratDev Digital Marketing — Knowcap Relationship - -**Status:** Restart in progress (paused Feb 2026, re-engaging May 21, 2026) -**Launch window:** End of July 2026 -**Credits available:** ~2 months of unused service per Feb 2026 pause arrangement - -> **Naming note:** Hassan sometimes refers to this agency as "StartDev" — the actual company name is **StratDev** (Strategy Development) Digital Marketing. Search Gmail with `stratdev` not `startdev`. - -## Company info - -- **Name:** StratDev Digital Marketing (LLC, acquired Feb 2026 by HSR Capital) -- **Domain:** stratdevdigitalmarketing.com -- **Slack:** stratdevagency.slack.com (Hassan added as guest at hsa@knowcap.ai) -- **Service scope:** Meta Ads + Landing Pages for Knowcap launch - -## Key contacts - -| Person | Email | Role | -|---|---|---| -| **Harish Ramachandran** | harish@stratdevdigitalmarketing.com | New owner (HSR Capital, acquired Feb 2026) — decision-maker on credits + billing | -| **Freddie Francis** | freddie@stratdevdigitalmarketing.com | Director of Client Growth — original sales partner, sent recent RFP-2026 | -| **Matt Scarpa** | matt@stratdevdigitalmarketing.com | Client Success Manager — day-to-day ops | -| **Jordan Calderon** | jordan@stratdevdigitalmarketing.com | Signed original Marketing Agreement | -| Generic | hello@stratdevdigitalmarketing.com | Ops alias used by Freddie | - -## Timeline - -| Date | Event | -|---|---| -| 2025-09-30 | First 1:1 Strategy Session with Freddie | -| 2025-10-08 | Solutions Overview meeting | -| 2025-10-15–22 | Proposal review + red-line negotiations | -| 2025-10-23 | **Marketing Agreement SIGNED** (Knowcap x StratDev) | -| 2025-10-23 | First invoice issued ($1,625 setup deposit) | -| 2025-10-27 | Kick-off call | -| 2025-10-29 | Slack workspace setup | -| 2026-02-04 | **StratDev acquired by HSR Capital** — Harish becomes new owner | -| 2026-02-18 | Hassan emails Matt — **project PAUSED** ("internal priorities shifted") | -| 2026-02-22 | Harish offers credit-for-future-use on remaining 3-month minimum (generous given the ownership transition) | -| 2026-03-21 | Hassan accepts credit approach | -| 2026-03-21 | Hassan asks Harish to pause further billing | -| 2026-03-28 | Hassan asks to defer last billing | -| 2026-03-29 | Harish defers March 30 charge by one month | -| 2026-04-08 | Freddie sends new RFP-2026 contract (Docusign) — status unclear if signed | -| **2026-05-21** | **Hassan re-engages — launch locked for end of July, requesting meeting** | - -## Billing history (partial) - -- $1,625 setup deposit (Oct 2025) -- $1,625 (TBD — partial payment record from Mar 21 email) -- (Need full reconciliation from Harish — part of restart conversation) - -## What this folder is for - -Managing the entire StratDev relationship end-to-end: -- Strategy + plan for using their service -- Meeting notes -- Email correspondence -- Contracts + signed agreements (or references) -- Invoices + billing reconciliation - -## Files - -- **[plan.md](plan.md)** — How we want to use the credits + Knowcap launch marketing strategy -- **emails/** — Drafted and sent correspondence -- **meetings/** — Future meeting notes (empty until next call) -- **contracts/** — Signed agreements (empty stub) -- **invoices/** — Billing records (empty stub) diff --git a/docs/campaigns/stratdev/emails/2026-05-21-relaunch-meeting-request.md b/docs/campaigns/stratdev/emails/2026-05-21-relaunch-meeting-request.md deleted file mode 100644 index 12186f3..0000000 --- a/docs/campaigns/stratdev/emails/2026-05-21-relaunch-meeting-request.md +++ /dev/null @@ -1,29 +0,0 @@ -# Email — Relaunch + meeting request to StratDev - -**Date:** 2026-05-21 -**From:** Hassan (hsa@smetools.io) -**To:** Harish Ramachandran (harish@stratdevdigitalmarketing.com), Freddie Francis (freddie@stratdevdigitalmarketing.com) -**Cc:** Matt Scarpa (matt@stratdevdigitalmarketing.com) -**Subject:** Knowcap launch locked for end of July — let's get back to it -**Status:** Gmail draft created — ID `r2997160208853498512` — pending Hassan review + send - ---- - -Hi Harish, Freddie, Matt, - -Hope you're all well. Quick update — we've locked the Knowcap V2 launch window for **end of July**, and I want to get StratDev back in motion to support the marketing push. - -First, **genuine thanks for the credits arrangement** when we paused in February. That was a generous and pragmatic call from your end, especially during the ownership transition — really appreciated. We'd like to use those credits now to fuel the launch. - -A couple of things I'd like to set up: - -**1. A 30-45 min briefing call** — the product is in a meaningfully different place than when we paused in Feb. I've been heads-down building V2, the positioning has sharpened, and the ICP is clearer. I want to walk your team through where Knowcap actually is now, who we're targeting, and how that should shape the Meta ads + landing page work. The brief from October is partially outdated. - -**2. A quick reconciliation on where we stand** — remaining credit balance, what's still in scope from the original Marketing Agreement, and whether the RFP-2026 Freddie sent in April supersedes anything. Want to make sure we're aligned before restart. - -Book directly on my calendar: https://calendly.com/smetools/meeting-with-hassan — or reply with what works for you next week (May 25–29) and we'll find a slot. - -Looking forward to getting this rolling again. - -Talk soon, -Hassan diff --git a/docs/campaigns/stratdev/plan.md b/docs/campaigns/stratdev/plan.md deleted file mode 100644 index a53f5a5..0000000 --- a/docs/campaigns/stratdev/plan.md +++ /dev/null @@ -1,95 +0,0 @@ -# StratDev Relaunch Plan — Knowcap Launch Marketing - -**Date:** 2026-05-21 -**Owner:** Hassan -**Status:** Re-engaging after Feb 2026 pause; launch locked end of July - -## Context for the restart - -The pause in February was triggered by internal priorities shifting (Knowcap product wasn't ready for paid acquisition yet — Hassan was deep in V2 dev). Now in May, the picture is different: - -1. **Knowcap V2 launching end of July** — non-negotiable date -2. **Hassan has built most of V2 himself** with Claude Code — product is in a meaningfully different place than Feb -3. **Positioning sharpened** — "verified facts vs claims" thesis post-2026-05-12 (read.ai analysis confirmed Knowcap's REST-backfill differentiator) -4. **ICP cleaner** — agent-mode operators, mid-market ops/sales/CS teams using Meet/Zoom heavily -5. **Distribution thesis evolved** — product-led growth via every meeting Knowcap touches creates artifacts visible to other attendees (built-in viral loop) - -The restart isn't "let's pick up where we left off." It's "the product is different, the positioning is sharper — let's brief your team on what we're actually marketing now." - -## What we want from StratDev - -Per the original Oct 2025 scope: **Meta Ads + Landing Pages**. - -Specifically over June-July: -- **Meta Ads:** Paid acquisition targeting Knowcap ICP (ops/sales/CS teams using meeting platforms, founders/PMs) -- **Landing Pages:** Conversion-optimized pages for the new positioning ("verified facts vs claims" thesis), with proper attribution -- **A/B testing infrastructure** to validate which positioning hooks convert -- **Retargeting** for visitors who engage but don't convert immediately - -## Using the credits - -Per Harish's Feb 22, 2026 offer: -- 3-month minimum term contractually committed -- Only first month was fully delivered at pause -- Remaining months → credited for future use - -We want to use those credits now. Need from Harish: -- Confirmed remaining credit balance -- What's still in scope from the original Marketing Agreement -- Whether the April 8 RFP-2026 (new contract from Freddie) supersedes the original — and if so, what does the credit balance look like under the new contract - -## What we'll bring to the briefing call - -1. **Product walkthrough** — show Knowcap V2 in action, not just slides -2. **Positioning brief** — the "verified facts vs claims" thesis, why it matters for the ICP -3. **ICP definition** — who we're targeting, what triggers they have, what's broken in their current workflow -4. **Competitive landscape** — read.ai, Fireflies, Otter, Granola, Notetaker, what makes Knowcap different -5. **Launch timeline** — end of July soft launch, content + paid acquisition runway, success metrics -6. **Budget framing** — what we want to spend per channel over the launch window - -## Risk register - -| Risk | Mitigation | -|---|---| -| StratDev's April RFP-2026 contract isn't compatible with original credits | Discuss in restart meeting — need transparent reconciliation | -| Harish wants new committed minimum to use credits | Negotiate: credit + month-to-month going forward, no new minimum | -| Meta ads can't scale Knowcap fast enough by July | Run paid as supplement to founder-led organic; don't rely 100% on StratDev for launch volume | -| StratDev's playbook is e-commerce / B2C — Knowcap is B2B SaaS | Brief them hard on the SaaS funnel; consider second specialist agency if needed for content/distribution | -| Knowcap launch slips → StratDev spend is wasted | Lock launch date end of July; only restart paid ads 2 weeks before launch (mid-July) | - -## Phased execution - -**Phase 1 — Re-alignment (May 22 – June 5)** -- Briefing call with StratDev team -- Credit reconciliation in writing -- Updated scope + positioning brief delivered to StratDev -- Landing page wireframes from StratDev - -**Phase 2 — Landing page build + creative (June 6 – June 30)** -- StratDev builds landing pages -- Creative production (ad variants) -- Tracking + attribution setup -- Soft test ad to small budget to validate setup - -**Phase 3 — Launch ramp (July 1 – July 31)** -- Mid-July: full launch -- Paid acquisition scales -- Daily monitoring + iteration -- StratDev weekly reporting - -**Phase 4 — Post-launch evaluation (Aug 1+)** -- Decide: continue with StratDev, switch agencies, or in-source -- Depends on: CAC, LTV signal, qualified pipeline volume - -## Decision points - -- **End of May briefing:** Does StratDev's team get the SaaS thesis quickly? (Original work was promising on landing pages, weaker on B2B targeting) -- **Mid-June:** Are landing pages built and converting at a baseline rate (>2%)? -- **End of July launch:** Did paid acquisition deliver qualified pipeline? Or is Knowcap distribution mostly organic/founder-led? -- **End of August:** Continue, switch, or end the relationship? - -## Cross-references - -- [Full email history + relationship status](README.md) -- [Knowcap V2 strategy](file:///C:/Users/Eng.Hassan/Github/arslan-ventures/av-claude-workspace/docs/knowcap-two-sku-strategy.md) -- read.ai competitive analysis: `~/Github/knowledge/llm-wiki/wiki/Knowcap/competitors/read.ai/architecture.md` diff --git a/docs/content-pipeline/README.md b/docs/content-pipeline/README.md deleted file mode 100644 index 83d6202..0000000 --- a/docs/content-pipeline/README.md +++ /dev/null @@ -1,12 +0,0 @@ -# Content Pipeline - -Blog drafts before they ship. - -| Folder | What | -|---|---| -| `strategy/` | Content strategy + marketing content plan | -| `drafts/` | In-progress posts | -| `ideas/` | Concepts pre-draft | -| `video/` | Video briefs (demo, animated) | - -When a draft is approved, move it to `app/content/blog/.md` so the Next.js site renders it. diff --git a/docs/content-pipeline/drafts/commitment-linkedin.md b/docs/content-pipeline/drafts/commitment-linkedin.md deleted file mode 100644 index 5c3a0e5..0000000 --- a/docs/content-pipeline/drafts/commitment-linkedin.md +++ /dev/null @@ -1,93 +0,0 @@ -# LinkedIn Post — Commitment Layer - -**Status:** Draft 1 — 2026-06-04 -**Surface:** LinkedIn (Hassan's personal profile) -**Char count target:** ~1400 (sweet spot for long-form LinkedIn) - ---- - -Tom Blomfield (YC partner, Monzo co-founder) just stopped me cold. - -Watch it here → https://www.youtube.com/shorts/IaWIazkWWog - ---- - -"The biggest blocker to AI automation of companies is no longer the models. Now, the real blocker is the domain knowledge inside companies." - -Every business has critical know-how scattered everywhere. -People's heads. Email threads. Slack. Support tickets. Databases. - -The company only works because humans vaguely remember where that knowledge is — and how to apply it. - -AI agents can't operate like that. - -He calls what we need "a company brain" — a living map of how the company actually works. -Not a search tool. Not a chatbot over documents. -Something that pulls the knowledge out of the fragmented sources, structures it, keeps it current, and turns it into executable context for AI agents. - -That framing unlocked something for me. - ---- - -Because I'd add one layer on top of it. - -The deepest form of company knowledge isn't policies or procedures. -It's commitments. - -Every company is making hundreds of promises a week. - -To clients. To employees. To partners. To suppliers. - -Your client was promised delivery by June. -Your team lead committed to having the feature ready for the demo. -Your supplier gave you lead times the whole schedule depends on. - -None of it lives anywhere structured. -It lives in conversations — recordings, voice notes, WhatsApp threads. - -And when it breaks, nobody saw it coming. -Because there was never a system watching it. - -That's not a project management problem. -That's an open loop. - ---- - -The tools that tried to close this gap all died the same way. - -RAID logs. Action-item trackers. Contract management systems. -They captured the right things — commitments, risks, decisions, tasks. -They all collapsed for the same reason: they required humans to manually maintain them. - -You can't add discipline on top of existing work. -You have to remove the friction until the discipline becomes automatic. - ---- - -What I'm most excited about in AI is exactly this. - -A system that listens to every meeting and extracts every commitment spoken aloud. -Flags every risk surfacing against those commitments. -Turns every mitigation into tracked tasks. -And surfaces everything to a named human for confirmation before acting on it. - -Because a closed loop system that acts on unverified data isn't intelligence. -It's noise. - -The human judgment stays in the loop. -The machine handles everything else. - ---- - -Organizations aren't hierarchies. -They're webs of commitments. - -AI is finally about to make sure they're kept. - ---- - -*Notes for posting:* -- Post from Hassan's personal LinkedIn — founder thought leadership, no product mention -- Best time: Sunday 9am or Monday 8am Cairo time -- Max 3 hashtags: #AIagents #AIstartups #FutureOfWork -- First comment: "This is the problem we're solving at Knowcap — if you want to see what the closed loop looks like in practice, DM me." diff --git a/docs/content-pipeline/drafts/commitment-thesis.md b/docs/content-pipeline/drafts/commitment-thesis.md deleted file mode 100644 index d5e5870..0000000 --- a/docs/content-pipeline/drafts/commitment-thesis.md +++ /dev/null @@ -1,40 +0,0 @@ -# The Commitment Layer — Mini Blog Draft - -**Status:** Draft 1 — 2026-06-04 -**Intended surface:** Blog, LinkedIn long-form, About page, investor narrative -**Author:** Hassan Arslan - ---- - -## Every organization is a web of commitments. - -You made one to your client when you promised the project would be done by June. You made another to your manager when you said the weekly report would land every Thursday. Your supplier made one to you when they agreed on lead times. Your team lead made one when she said the new feature would be ready for the demo. - -None of these commitments live in your project management tool. They live in the conversation — the call recording, the meeting transcript, the voice note, the WhatsApp thread. And because they live there, they die there. The risk materializes quietly. The deadline slips. The scope expands. And by the time anyone notices, the commitment has already been broken. - -This is the core problem Knowcap was built to solve. - -**An organization isn't a hierarchy. It's a web of commitments** — internal promises between employees and managers, and external promises to clients, partners, and suppliers. Every commitment carries risk. Scope creep is a request with no matching commitment backing it. A supplier delay is a risk threatening an after-sales commitment. An unreported bottleneck is a risk against every downstream commitment that depends on it. Commitments are the unit of organizational accountability, and risk is what threatens them. - -Knowcap captures all of it — automatically, from the conversations your team is already having. Every commitment spoken aloud gets extracted, attributed to its speaker, and linked to the relevant project. Every risk that surfaces against it gets flagged. Every decision made to mitigate it gets logged. Every task that fulfils it gets tracked. And every one of those extractions gets surfaced to a human for confirmation before an agent is allowed to act on it — because a system that acts on unverified data isn't intelligence, it's noise. - -That last part is the moat. RAID logs exist. Action-item trackers exist. Contract lifecycle management tools exist. Every operations methodology since PMBOK has tried to capture commitments, risks, decisions, and tasks. They all failed at the same point: they required humans to manually maintain them. The discipline collapsed under the weight of actual work. - -Knowcap inverts that. The discipline is automatic. The human judgment is what remains — the confirmation step that turns an AI extraction into a verified fact your agents can act on. That confirm-then-act loop isn't a UX detail. It's the product. - -The result: a living map of every promise your organization has made, every risk threatening those promises, and every action being taken to honour them. Not as a dashboard you build. As a byproduct of the conversations you're already having. - ---- - -## LinkedIn post (short-form) - -See `commitment-linkedin.md` in this folder. - ---- - -## Notes for editing - -- The Odoo partner angle: a commitment in a consulting engagement is a SOW line. When a client asks for something outside scope, it's a risk against the original commitment. Knowcap flags it and generates the change-order conversation automatically. -- Real examples from Ariika data: "weekly report every Thursday" (internal commitment, manager→employee), "finalize SO immediately" (external commitment, Dana→client), supplier non-compliance (risk against after-sales commitment). -- The "organizations as web of commitments" framing is original — doesn't appear verbatim in CLM or PMBOK literature. Worth protecting. -- The RAID log reference (Risk, Assumption, Issue, Decision) connects to project management canon without naming the acronym. Intentional — keeps the writing accessible. diff --git a/docs/content-pipeline/drafts/commitment-visual.html b/docs/content-pipeline/drafts/commitment-visual.html deleted file mode 100644 index 9791cc6..0000000 --- a/docs/content-pipeline/drafts/commitment-visual.html +++ /dev/null @@ -1,391 +0,0 @@ - - - - - -Organizations are webs of commitments - - - -
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    - - diff --git a/docs/content-pipeline/drafts/homepage-commitment-copy.md b/docs/content-pipeline/drafts/homepage-commitment-copy.md deleted file mode 100644 index af4001b..0000000 --- a/docs/content-pipeline/drafts/homepage-commitment-copy.md +++ /dev/null @@ -1,170 +0,0 @@ -# Homepage Copy — Commitment Edition (full replacement) - -**Status:** Draft 1 — 2026-06-10 -**Replaces:** version-b (outcome) + version-d (magic) A/B rotation -**Source:** commitment-thesis.md + .agents/product-marketing.md + POSITIONING.md locked sentences -**Pipeline:** copywriting → ogilvy → stop-slop applied. Pending: great-web-copy score gate. - ---- - -## HERO - -**Kicker (mono):** Knowcap · MCP server for Claude, Codex & Gemini - -**H1 (locked by Hassan 2026-06-10 after skill audit):** -> Your company's deepest knowledge -> is its commitments and the risks against them. -> **Knowcap makes sure they're kept.** - -**Subheadline:** -> Your client was promised delivery by June. Your team lead promised the demo would work. Those promises live in conversations, and they die there. Knowcap captures every commitment spoken aloud, flags every risk against it, and lets your AI agents act on it — after a named human confirms it. - -**Doctrine line (mono card, under sub — locked sentence #2 verbatim):** -> Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true. - -**CTAs:** [Get Started Free] [Book a Demo] - -**Capture bullets:** -- ✓ Capture meetings, recordings, voice notes, documents, URLs, and Telegram -- ✓ AI extracts every commitment, decision, task, and risk — with the speaker and the timestamp - -**Trust strip:** Built by an Odoo partner · MCP-native · Full audit trail on every action - -**Hero exhibit (ClaimsExhibit cards, live-meeting feel):** -- 0:14:32 · Client — "We need this live before Ramadan." → tag: commitment · ⏳ pending your confirm -- 0:14:33 · Knowcap — Linked to project Atlas-ERP. Conflicts with the supplier lead time confirmed last week. → tag: risk · ⏳ pending -- 0:14:35 · You — one tap → ✓ Verified · agent drafts the change-order email - ---- - -## SECTION 2 — PROBLEM ("What dies in the conversation") - -**H2:** The deadline slipped because the promise never lived anywhere. - -**Lead:** A company makes hundreds of promises a week. To clients. To employees. To suppliers. None of them live in your project tool. They live in calls, voice notes, and chat threads. When one breaks, you find out last. - -**3 cards:** - -1. **The client promise** - "We'll deliver by June." Said on a Zoom call. Never made it into the SOW. The scope grew, the date didn't move, and the margin paid for it. - -2. **The internal promise** - "It'll be ready for the demo." Said in standup. Slipped out of standup three weeks ago. The demo found out for you. - -3. **The supplier promise** - "Lead time is four weeks." Said on a phone call. Shipped in six. Your customer churned and your team never saw it coming. - -**Section close:** That is not a project-management problem. It is an open loop. Knowcap closes it. - ---- - -## SECTION 3 — HOW IT WORKS ("The loop") - -**H2:** Listen. Extract. Confirm. Act. - -**4 steps:** - -1. **Listen** — Knowcap captures the conversations your team is already having: meetings, recordings, voice notes, documents, Telegram. -2. **Extract** — AI pulls out every commitment, decision, task, and risk. Each one carries its speaker and a timestamp back to the exact second it was said. -3. **Confirm** — A named human reviews each claim and promotes it to evidence with one tap. No bulk approve. No silent ingestion. The graph holds what your team confirmed, nothing else. -4. **Act** — Agents work from confirmed facts: draft the change-order email, create the Odoo task, brief the next meeting. Every action carries its receipts. - -**Footnote (mono):** Confirmation takes about two minutes per meeting. The agent actions it unlocks run before the meeting ends. - ---- - -## SECTION 4 — THE 80-SECOND STORY (Odoo demo, truthful version) - -**Figure:** 80 seconds -**H3:** Meeting → confirmed scope change → Odoo task. - -**Body:** Your client says "add the warehouse module to phase two." Knowcap captures it, timestamps it, classifies it as a scope decision, and puts it in your inbox. You confirm with one tap. Before the meeting ends, the task is in your Odoo project with the client's exact words attached — and the change-order conversation is already drafted. - -**Caption (Ogilvy: caption = miniature ad):** Scope creep is a request with no commitment backing it. Knowcap flags the gap while the client is still on the call. - ---- - -## SECTION 5 — WHY EVERYTHING BEFORE THIS FAILED - -**H2:** RAID logs, action trackers, contract tools — they all died the same way. - -**Body:** -They captured the right things: commitments, risks, decisions, tasks. They all collapsed at the same point: a human had to maintain them by hand. The discipline lasted two sprints and then real work won. - -You can't add discipline on top of existing work. You have to remove the friction until the discipline becomes automatic. - -Knowcap inverts the old model. The capture is automatic. The judgment stays human: one tap that turns an AI extraction into a fact your agents can rely on. That confirm-then-act loop is not a UX detail. It is the product. - -**Proof bar (3 stats):** -- 52% of agency projects hit scope creep -- 70% of meeting decisions are forgotten within 24 hours -- 15 competitor products examined. Zero verify facts with a named human. - ---- - -## SECTION 6 — MCP / "IN YOUR CLAUDE" (B2C anchor) - -**H2:** Your agents, your tools, your verified facts. - -**Body:** Knowcap ships as an MCP server. Connect it to Claude, Codex, or Gemini and your agents query your organization's confirmed knowledge — `search_memories(verification_strictness='human_only')` — instead of guessing from transcripts. Ask what was promised to a client, what risks are open against the launch, what changed since last week. The answers come with receipts: who said it, when, and who confirmed it. - -**Bullets:** -- ✓ Works inside the AI tools you already use -- ✓ Agents read confirmed facts only — strictness is enforced server-side, per agent -- ✓ Every fact links back to the second it was said - -**CTA:** [Connect Your Claude →] - ---- - -## SECTION 7 — FAQ (objection handling) - -**Q: Isn't this another meeting notetaker?** -Notetakers hand you a summary and stop. Knowcap is the layer after the summary: every extracted claim is confirmed by a named human, becomes part of your organization's verified memory, and is served to your AI agents with an audit trail. Summaries are the input. Kept commitments are the output. - -**Q: Confirming every claim sounds like work.** -It is about two minutes per meeting, one tap per claim. That is the entire human cost of agents that act on truth instead of guesses. And there is no "confirm all" button — by design. One bulk approve would poison the whole graph. - -**Q: What about our data?** -Your graph is scoped to your organization. Agents see only what their API key allows, at the strictness tier you set. Every confirmation is logged: who, what, when, against which source. Built for Saudi PDPL and GDPR Article 22 from day one. - -**Q: Which tools does it work with?** -Claude, Codex, and Gemini today via MCP. Capture from Google Meet, uploaded recordings, voice notes, documents, URLs, and Telegram. Odoo task creation for implementation teams. - ---- - -## SECTION 8 — CLOSER (dark, mirrors hero) - -**H2:** -> Organizations aren't hierarchies. -> They're webs of commitments. - -**Sub:** AI is finally able to make sure they're kept. - -**CTAs:** [Get Started Free] [Book a Demo] - -**Footer brand line (locked sentence #3 verbatim):** Knowcap is verified knowledge for AI agents. Humans confirm. Agents act. - ---- - -## META - -**Title:** Knowcap — Every company is a web of commitments. Knowcap makes sure they're kept. -**Description:** Knowcap captures every commitment, decision, task, and risk from your meetings and chats. A named human confirms each one. Your AI agents act on verified facts only — with a full audit trail. - ---- - -## Annotations (why) - -- **H1** = commitment thesis (POSITIONING.md center of gravity, 2026-06-04). 12 words, brand + promise (Ogilvy). "Company" over "organization": shorter, warmer. -- **Locked sentence #2** kept verbatim as doctrine line in hero block (POSITIONING.md assigns it to landing hero; surfaced as mono card so both the thesis H1 and the locked line are above the fold). -- **Odoo story** rewritten task-version: VISION.md 2026-05-29 killed the auto-PR demo. Old live copy promised a PR — vapor, now removed. -- **Capture list** truthful: dropped WhatsApp/Zoom/Teams/Slack claims from old variants (not shipped). Meet + recordings + uploads + URL + text + Telegram only. -- **No commitment-as-category claim**: copy says Knowcap "captures commitments" (true — they land inside decisions/tasks today) without showing a Commitment product category (schema ADR still pending). -- **Stop-slop pass:** no "unlock/seamless/supercharge", no rhetorical setups, em dashes minimized, active voice, facts over adjectives. Locked sentences + Hassan's signature closer kept verbatim (signature lines override style rules). - -## Headline alternatives (if Hassan wants options) - -- A (chosen): "Every company is a web of commitments. Knowcap makes sure they're kept." -- B: "Your company runs on promises made in meetings. Knowcap keeps every one." — plainer, less IP-flavored -- C: "Hundreds of promises a week live in your meetings. Knowcap makes sure they're kept." — quantified, longer diff --git a/docs/content-pipeline/ideas/README.md b/docs/content-pipeline/ideas/README.md deleted file mode 100644 index a638cfd..0000000 --- a/docs/content-pipeline/ideas/README.md +++ /dev/null @@ -1,7 +0,0 @@ -# Content Ideas - -Folder for show concepts, video ideas, and creative pitches. - -| Folder | Concept | -|---|---| -| `aid-mockumentary/` | "AI'd" — Ariika employees forced to route every decision through AI for one week. Shot via smart sunglasses POV. | diff --git a/docs/content-pipeline/ideas/aid-mockumentary/characters.md b/docs/content-pipeline/ideas/aid-mockumentary/characters.md deleted file mode 100644 index 5729b4f..0000000 --- a/docs/content-pipeline/ideas/aid-mockumentary/characters.md +++ /dev/null @@ -1,33 +0,0 @@ -# AI'd — Cast Archetypes - -Six characters. Tito + Mariam = the system. Yara + Karim = the resistance. Hany = chaos neutral. Omar = the audience. - -## Omar Tawfik (32) — Operations Manager / Narrator -The reluctant documentarian. Wears the smart sunglasses because his manager told him to "explore wearable AI for the team." Uses them to passively film everyone instead. Outwardly compliant, inwardly cataloguing evidence for the inevitable HBO documentary. His one rule: never let the AI catch him not using the AI. - -**Runner:** Talks to his sunglasses like they're a confidant. They occasionally talk back. He's not sure if he likes that. - -## Yara Hosny (27) — Brand Designer -The casualty. Genuinely talented, watching her job get reduced to "prompt engineer for a machine that thinks beanbags should look like the Suez Canal." Starts the season fighting back. Mid-season, gives up and starts producing AI slop on purpose to see if anyone notices. They don't. She gets promoted. - -**Runner:** Her rejected human-made designs keep showing up taped inside bathroom stalls. Someone is curating a guerrilla gallery. We never find out who. - -## Tarek "Tito" Nour (41) — VP of Growth -The True Believer. Has named his AI "Vision." Refers to Vision in meetings as "my collaborator." Once said "Vision and I had a breakthrough at 3am" with full sincerity. Quotes LinkedIn posts as if they're scripture. Almost certainly the most dangerous person in the building. - -**Runner:** Slowly starts dressing like his AI's avatar. Nobody comments. It gets worse every episode. - -## Mariam El-Sayed (29) — HR Business Partner -The enforcer. Tasked with rolling out Project Synapse. Genuinely believes she's helping. Has a whiteboard tracking "AI Adoption Velocity." Doesn't understand why morale is dropping when the dashboard says everyone's "engaged." Her empathy is real, her tools are not. - -**Runner:** Her AI-generated "wellness check-ins" get progressively more menacing. By episode four it's just sending people the eye emoji at midnight. - -## Hany Abdel-Aziz (58) — Warehouse Operations Lead -The Old Guard. Has worked at Ariika since the beanbag was invented. Refuses to use the AI. Gets sent to mandatory AI training. Through sheer stubbornness and shouting at the screen, becomes accidentally world-class at prompt engineering. Now everyone comes to him. He hates this. - -**Runner:** His prompts are all in Arabic, all profane, and produce shockingly elegant results. Subtitles can't keep up. - -## Karim Fahmy (24) — Junior Marketing Associate -The saboteur. Spotted early that the AI has no idea what's real. Spends his days feeding it lies — fake KPIs, fictional coworkers, made-up company history — to see how far they propagate. By mid-season the AI is confidently citing "Q3 success metrics from our Aswan office." Ariika has no Aswan office. - -**Runner:** He's keeping a private leaderboard of which lies have made it into actual board decks. He's winning. diff --git a/docs/content-pipeline/ideas/aid-mockumentary/concept.md b/docs/content-pipeline/ideas/aid-mockumentary/concept.md deleted file mode 100644 index 05fa597..0000000 --- a/docs/content-pipeline/ideas/aid-mockumentary/concept.md +++ /dev/null @@ -1,25 +0,0 @@ -# AI'd — Show Concept - -**Logline:** Ariika rolls out a company-wide mandate: every decision, conversation, and creative call must be run through AI for one week. One employee documents the chaos through their smart sunglasses. - -**Format:** 22-min single-cam mockumentary. POV-cam (Ray-Ban Meta sunglasses) hybrid with traditional talking-head confessionals. - -**Tone reference:** Nathan For You meets The Office meets Black Mirror's lighter episodes. - -## Why this works -- Built-in meta layer: the sunglasses are AI-powered, so the wearer is also being AI'd while filming colleagues being AI'd. -- Visual constraint = comedy. Shaky head turns, awkward eyeline, accidentally filming the floor during a confrontation. The "bad camera" becomes a character. -- Ariika as the fictional employer gives a real e-commerce/lifestyle brand backdrop to ground the absurdity. - -## Comedic engine -A rule + a constraint. The rule: "every decision must route through AI." The constraints write themselves — AI hallucinates Ariika-internal details, escalates conflicts, reduces creative work to slop, treats lunch orders like geopolitical negotiations. - -## Recurring bits to seed -- AI-generated motivational posters that get progressively unhinged. -- A Slack channel called `#ai-says` where employees post the worst suggestions. -- One employee secretly thriving under AI rule. Everyone hates him. - -## Production notes -- Meta Ray-Bans cap at ~3 min clips, 1080p — plan shot lists around the limit. -- AI overlays added in post: live transcription floating over heads, sentiment labels ("PASSIVE-AGGRESSIVE: 87%"), real-time translation of corporate-speak into plain English. -- If real Ariika employees appear (vs actors), get written releases before filming. Egyptian recording/consent law applies. diff --git a/docs/content-pipeline/ideas/aid-mockumentary/pilot-treatment.md b/docs/content-pipeline/ideas/aid-mockumentary/pilot-treatment.md deleted file mode 100644 index 21650b0..0000000 --- a/docs/content-pipeline/ideas/aid-mockumentary/pilot-treatment.md +++ /dev/null @@ -1,28 +0,0 @@ -# AI'd — Pilot Treatment - -22-minute single-cam mockumentary. Shot mostly through Omar's Ray-Ban Metas, intercut with talking-head confessionals. - -## Cold Open (2 min) -Omar adjusts his sunglasses in the bathroom mirror. To camera (his reflection): "Day one. They said embrace AI or get left behind. So I'm embracing it. With my face." - -Cut to all-hands meeting. CEO unveils "Project Synapse." A junior designer raises her hand to ask a question — HR cuts her off: "Please route that through the AI." She types. AI responds: "Your question has been deemed redundant." She sits down. - -Title card. - -## Sketch 1 — "The Beanbag Brief" (5 min) -Product team must design a new beanbag. Rule: only AI-generated concepts allowed. The AI keeps producing beanbags shaped like geopolitical conflicts. "This one is called 'The Suez.'" Marketing lead loves it. Designer quietly weeps. - -Sunglasses-cam catches her drafting a resignation letter — which the AI auto-improves into a promotion request. - -## Sketch 2 — "Conflict Resolution" (5 min) -Two coworkers fight over a parking spot. HR mandates AI mediation. The AI, trained on Reddit, escalates everything. By minute three it's suggesting a duel. By minute five they're friends again because they both hate the AI more than each other. - -Real bonding moment. - -## Sketch 3 — "The Lunch Order" (5 min) -Office lunch must be ordered via AI consensus. AI polls 47 employees, factors in dietary restrictions, weather, and "team morale metrics." Final recommendation: one (1) boiled egg, split 47 ways. - -Omar's sunglasses run out of battery mid-meltdown. Hard cut to black, audio only. Someone is crying. Someone else is laughing. The AI says "resolution achieved." - -## Tag (2 min) -Omar at home, sunglasses still on, talking to his wife. She asks how his day was. He opens his mouth — pauses — pulls out his phone, types the question into ChatGPT, reads the answer aloud. She stares at him. Smash cut to credits. diff --git a/docs/content-pipeline/strategy/marketing-content-plan.md b/docs/content-pipeline/strategy/marketing-content-plan.md deleted file mode 100644 index 2a7b46d..0000000 --- a/docs/content-pipeline/strategy/marketing-content-plan.md +++ /dev/null @@ -1,283 +0,0 @@ ---- -title: "Marketing + Content Plan — Post-Council Reset" -type: article -company: Knowcap -confidence: high -status: developing -decisions: ["[[wiki/Knowcap/decisions/2026-05-25 - Strategic Council - Vision Thesis Stress Test]]"] -created: 2026-05-25 -updated: 2026-05-25 -tags: [marketing, content, budget, 90-day-plan] ---- - -# Knowcap Marketing + Content Plan — Post-Council Reset - -Built May 25, 2026 after the 16-agent strategic council. Replaces the content angles from the May 6 voice memo (which used the old "trust layer" framing). Budget and hour envelope from the locked 90-day plan (May 21) still hold. - ---- - -## Budget + constraints - -| Item | Amount | Source | -|---|---|---| -| Paid ads | $2,000/month | StratDev (digital marketing agency) | -| Content creation | $0 (Hassan writes) | Founder-led, daily, not delegated | -| Video production | $0 (Knowcap + Higgsfield + Hyperframes) | Self-serve tools | -| Total monthly spend | $2,000 | Content has to carry the demand | - -| Constraint | Value | -|---|---| -| Working hours | 200h/month (Hassan) | -| Content hours | 35h/month (~1.5h/workday) | -| Marketing hours | 50h/month (StratDev coordination, positioning, landing page) | -| Sales hours | 35h/month (~1 call/workday + prep) | -| Dev hours | 15h/month (strategic only, June 1+) | -| Workweek | Sun–Thu (Fri/Sat OFF) | - ---- - -## Phase timeline (updated for current state) - -| Phase | Dates | Focus | Hassan's role | -|---|---|---|---| -| **Sprint** (current) | May 22 – Jun 7 | Final dev push. Ship Skills sidebar + Odoo integration | Builder | -| **Bridge** | Jun 8 – Jun 21 | Content starts. Dev winds down. First 10 posts. StratDev kickoff | Builder → Storyteller | -| **Content-led** | Jun 22 – Jul 31 | Daily content. Sales calls start. $2K ads live | Storyteller + Seller | -| **Launch** | Jul 31 (peg on demo-readiness) | Public splash. Anchor "why now" to Saudi PDPL + GDPR Art 22 (EU AI Act Art 14 deferred to Dec 2027) | Launcher | - ---- - -## Content strategy — rebuilt around council findings - -> **Carry the moat in every track (added 2026-05-29).** The re-adjudication flagged that this plan frames Knowcap as a "meeting → content tool" and drops the verification thesis. Fix: every track lands the one differentiator no competitor has — *every fact confirmed by a named human, traceable to source; both sides confirm in cross-org.* Pain-led hook, moat-led proof. See [decision record](./decisions/2026-05-29-mena-council-readjudication.md). - -### The habit that makes everything else work - -Tag 2 content-worthy moments per meeting, every meeting, starting NOW. By June 1, you'll have 10-15 tagged moments ready. Without tags, Sunday = 3-hour transcript dig. With tags = 90-minute production session. - -Open Knowcap after every meeting, tag the 2 moments with the strongest hooks (real pain, real numbers, real stories), move on. 30 seconds per meeting. This is the one pre-June action that determines whether content production is a grind or a flow. - -### The 3 content tracks (replace the old 5×3 matrix) - -The old matrix (5 categories × 3 levels = 15 pieces) was product-feature-centric. The council showed that features don't sell — pain does. New tracks map to painkiller personas: - -#### Track 1: Agency/Consultancy pain (HIGHEST priority) - -**Why:** #1 painkiller persona. 52% of projects hit scope creep. $1-5K/month lost. Cross-org confirmation is unique. - -| # | Content piece | Format | Hook | -|---|---|---|---| -| 1 | "The $4,200 email no one sent" | Short video (Reel/TikTok) | Story: agency ate a scope change because no one documented the verbal agreement | -| 2 | "What if both sides confirmed the same thing?" | Explainer video | Cross-org confirmation demo — the feature nobody else has | -| 3 | "I run 3 companies. Here's how I lost a decision between meetings" | Personal story | Hassan's real experience — 70% of decisions forgotten in 24h | -| 4 | "Your follow-up email is not a contract" | Short video | The "as discussed" email doesn't hold up when the client disputes scope | -| 5 | "How we recovered 6 billable hours per consultant per week" | Case study | Auto-timesheets from meeting transcripts — ROI math | - -#### Track 2: Founder/CEO brain-replacement (HIGH priority) - -**Why:** #2 painkiller persona. Hassan IS the case study. Cross-company contradictions are existential. - -| # | Content piece | Format | Hook | -|---|---|---|---| -| 6 | "I have 3 companies and my brain was the only system of record" | Personal story | Before/after Knowcap — real meetings, real context | -| 7 | "The meeting where Company A contradicted Company B — and nobody caught it" | Story | Cross-company risk detection in action | -| 8 | "Why I built Knowcap: meetings are the biggest information contract in business" | Origin story | From the voice memo thesis — why meetings, not email, not Slack | -| 9 | "97.8% of AI memories are junk without human review" | Data-driven | The Mem0 stat — verification isn't optional, it's survival | -| 10 | "What Otter and Fireflies get wrong about meeting AI" | Hot take | Controversial: fire-and-forget is dangerous, not fast | - -#### Track 3: The product demo (builds credibility for both tracks) - -| # | Content piece | Format | Hook | -|---|---|---|---| -| 11 | "Meeting → verified decision → Odoo task in 90 seconds" | Screen recording | The confirmed-memory demo the council recommended | -| 12 | "How Knowcap watches your meeting — not just transcribes it" | Explainer | Vision pipeline: screenshots between text, timestamp links | -| 13 | "This is what happens when AI acts on unverified facts" | Story + data | Mem0 junk stat + Replit DB deletion incident + Air Canada ruling | -| 14 | "Knowcap vs Fireflies vs Otter — honest comparison" | Comparison video | We do verification; they don't. 0/15 competitors do | -| 15 | "Saudi PDPL + GDPR Article 22 already require a human in the loop — is your AI meeting tool ready?" | Thought leadership | Regulatory urgency on laws in force NOW (EU AI Act Art 14 deferred to Dec 2027) | - -### Weekly production schedule - -| Day | Activity | Time | -|---|---|---| -| **Sunday** | Select tagged meeting segments + write 2 LinkedIn posts (1 English, 1 Arabic) | 2.5h | -| **Monday** | Write 3rd LinkedIn post + schedule all 3 in Taplio + engagement round | 1.5h | -| **Tuesday** | (Week 3+) Record YouTube screen recording — Knowcap on screen, Hassan narrating | 3-4h | -| **Wednesday** | (Week 3+) Light edit YouTube + publish + LinkedIn engagement round | 1.5h | -| **Thursday** | LinkedIn engagement round + measurement ritual (Taplio / YouTube Studio / Stripe) | 1h | - -**Weeks 1-2: ~5h/week (LinkedIn only). Weeks 3-4: ~9h/week (LinkedIn + YouTube).** - -YouTube time budget: 3-4h per video, not 2h. Month 1 = zero-production screen recordings (3-5 min, Knowcap on screen, Hassan narrating). Graduate to polished HyperFrames + B-roll in month 2 only if weekly cadence holds. - -### Minimum viable content fallback - -When everything burns and you can't hit the full plan, the ONE thing that survives is: **1 LinkedIn post from a meeting transcript.** That takes 37 minutes. If you can't do 37 minutes, the week is lost — flag it in Thursday review and recover next week. Never zero. - -### Decision trigger - -**If 0 sales conversations by day 10, stop all content work.** Spend 3 days on direct WhatsApp outreach to the warm Odoo partner network. Content without pipeline is vanity. Resume content only after at least 1 real conversation is booked. - -### Platform priority - -| Platform | Format | Language | Cadence | Why | -|---|---|---|---|---| -| **LinkedIn** | Text posts + carousels | English | 3×/week | #1 for B2B leads. Taplio for scheduling + analytics | -| **LinkedIn (Arabic)** | Arabic post via Taplio | Arabic | 1×/week | MENA audience coverage without a separate platform | -| **YouTube** | Screen recordings (month 1: zero-production, 3-5 min, Knowcap on screen, Hassan narrating) | English | 1×/week (starts week 3) | SEO + evergreen discovery. Long-form authority | -| **X/Twitter** | Repurposed LinkedIn takes | English | Optional | Lower priority. Only if time permits | -| **Instagram** | -- | -- | Skip June | Revisit month 3. Not worth the overhead until LinkedIn + YouTube cadence holds | -| **TikTok** | -- | -- | Skip | Not B2B in MENA. Revisit post-launch | - ---- - -## Content source: Knowcap meeting recordings - -Hassan's daily meetings are the content mine. Every client call, strategy session, and product discussion is already recorded in Knowcap with full transcripts, verified decisions, and timestamped highlights. The content workflow extracts the best segments and branches them into three formats: - -**Pipeline: meeting → content** - -1. **Select segments** — browse Knowcap transcripts, pick the 2-3 moments with the strongest hooks (real stories, real numbers, real pain) -2. **Clean audio** — export audio clips, run through Adobe Podcast Enhance for studio-quality voice -3. **Branch into formats:** - - **YouTube** (faceless): screen recordings of Knowcap in action + clean audio voiceover. Month 1 = zero-production (3-5 min, Knowcap on screen, Hassan narrating). No talking head needed - - **LinkedIn (English)**: text posts pulling direct quotes and verified decisions from the transcript. Timestamp links back to Knowcap for credibility - - **LinkedIn (Arabic)**: 1 Arabic post per week via Taplio for MENA coverage -4. **The meta-play** — the content creation process itself demonstrates the product. "I used Knowcap to find this clip" IS the marketing - -This eliminates the blank-page problem. Hassan never has to invent content — every meeting generates 3-5 publishable moments. The bottleneck is editing, not ideation. - ---- - -## Tools + monthly spend - -| Tool | Cost | Purpose | -|---|---|---| -| Taplio | $39/mo | LinkedIn scheduling + analytics + content inspiration | -| Knowcap | $0 | Meeting → content extraction (our own product) | -| HyperFrames | $0 | Motion graphics / branded intros (month 2+) | -| Higgsfield | $0 (included) | AI video generation | -| Adobe Podcast (Enhance) | $0 (free tier) | Audio cleanup | -| **Total new spend** | **$39/mo** | | - ---- - -## Measurement (Thursday ritual, 30 min) - -No dashboards, no automated reports. Manual check every Thursday — 4 tabs open: - -1. **Taplio** — LinkedIn impressions, engagement rate, follower growth, best-performing post of the week -2. **YouTube Studio** — video views, watch time, subscriber delta, thumbnail CTR -3. **Stripe** — new customers, MRR movement, trial-to-paid conversion -4. **Timely** — hours spent per bucket (content / marketing / sales) vs target allocation - -Log numbers in the weekly scorecard (see june-2026-gtm-game.md). Kill underperforming content tracks, double down on what works. - ---- - -## Paid ads plan ($2K/month with StratDev) - -### One campaign, not three - -Scope Creep Insurance is the only campaign until it proves CPL under $10. Founder Brain and EU AI Act campaigns are deferred — they dilute the $2K budget across too many messages before any single one has proven conversion. - -### Budget split - -| Line item | Amount | Geo | Why | -|---|---|---|---| -| **Scope Creep Insurance** | $1,800 | Egypt + Saudi + UAE + UK/EU | One message, one landing page, one audience — agencies/consultants/Odoo partners | -| **LinkedIn retargeting** | $200 | People who engaged with organic LinkedIn content | Warm audience, cheapest conversion path | - -### Ad creative (1 campaign) - -| Campaign | Audience | Creative | CTA | -|---|---|---|---| -| **Scope creep insurance** | Agency owners, consultants, Odoo partners | "52% of projects hit scope creep. What if both sides confirmed the agreement?" | → Landing page: knowcap.ai/agencies | - -Kill/scale decision: if Scope Creep CPL is under $10 after 2 weeks, scale it and consider adding Founder Brain as campaign #2. If CPL is over $15, pause paid and double down on organic + direct outreach. - -### StratDev deliverables per month - -| Week | StratDev does | Hassan does | -|---|---|---| -| 1 | Campaign setup, audience targeting, pixel | Approve creatives, provide video assets | -| 2 | A/B test copy + audiences | Review performance, approve winners | -| 3 | Scale winners, kill losers | Provide new content for next test batch | -| 4 | Monthly report + optimization plan | Approve next month's direction | - ---- - -## Sales plan (35h/month, June 22+) - -### Week 1-4 targets - -| Week | Content | Sales | Marketing | -|---|---|---|---| -| 1 | 3 LinkedIn posts. Taplio setup | Identify 10 Odoo partners | ONE StratDev campaign submitted (Scope Creep) | -| 2 | 3 LinkedIn posts | Outreach to 5 warm contacts. Decision trigger active (0 conversations by day 10 = pivot) | Campaign goes live | -| 3 | 3 LinkedIn posts + first YouTube (ugly screen recording) | Demo Knowcap to interested partners | Campaign optimizing | -| 4 | 3 LinkedIn posts + second YouTube. Thursday measurement | Follow up + close first pilot | Kill/scale decision on campaign CPL | - -### The pitch (30-second version) - -For agencies/consultancies: -> "After your client meeting, both you and the client see the same verified decisions. No more 'I never agreed to that.' Your team saves 6 hours a week on meeting admin, and scope disputes drop to zero. It plugs into the Odoo you already sell." - -For founders: -> "After 50 meetings across your companies, Knowcap knows every decision, every commitment, every risk — and it's all been checked by a human. Your next proposal references 6 months of verified client history, not yesterday's memory." - -### Distribution channel: Odoo partner network - -| Action | Timeline | Goal | -|---|---|---| -| Pick 10 partners Hassan knows | Week 1 | Warm list | -| Free 3-month access for 5 partners | Week 2-3 | Case study pipeline | -| Case study from first 3 partners | Month 2 | Sales collateral | -| Odoo App Store listing | Month 2 | Passive discovery | -| Partner reseller program (20-30% rev share) | Month 3 | Scale distribution | - ---- - -## 90-day milestones (updated) - -| Milestone | Date | Status | -|---|---|---| -| Skills sidebar shipped (hassan branch) | Jun 7 | Not started | -| Odoo integration live | Jun 14 | Not started | -| First 10 content pieces published | Jun 21 | Not started | -| StratDev campaigns live ($2K) | Jun 22 | Not started | -| "Confirmed memory" 90-second demo video | Jun 28 | Not started | -| Regulatory brief published (Saudi PDPL + GDPR Art 22; EU AI Act Art 14 as 2027 tailwind) | Jul 6 | Not started | -| 3 paying Odoo partners | Jul 15 | Not started | -| Saudi PDPL compliance positioning filed | Jul 21 | Not started | -| 50 content pieces published | Jul 31 | Not started | -| **PUBLIC LAUNCH** | Jul 31 | Not started | - ---- - -## The one-page pitch (for landing pages + StratDev briefs) - -**Headline:** Your meetings become institutional memory your whole team can trust. - -**Subhead:** Knowcap records, transcribes, and extracts every decision, risk, and commitment — then a human confirms each one before any AI acts on it. After 50 meetings, your team has a verified knowledge base no other tool can match. - -**Product DNA:** Otter + Loom + NotebookLM — verified. - -**The number:** 97.8% of AI-extracted memories are junk without human review (Mem0 production audit, 2026). - -**3 bullets:** -1. **Both sides confirm.** When you meet with a client, both of you verify the same decision. No more "I never agreed to that." -2. **Skills act on verified facts only.** Automated follow-ups, CRM updates, Odoo tasks — all grounded in what a human confirmed, not what AI guessed. -3. **The graph compounds.** After 100 meetings, your AI has context across every conversation, every relationship, every commitment — verified. - -**CTA:** Start free → knowcap.ai - ---- - -## What this plan does NOT cover (defer to later) - -- Mobile app marketing -- Developer marketing (API/MCP) -- Enterprise sales motion (>50 seats) -- Conference sponsorships -- Influencer partnerships -- PR/press outreach (save for launch day) diff --git a/docs/content-pipeline/video/demo-video-strategy.md b/docs/content-pipeline/video/demo-video-strategy.md deleted file mode 100644 index d0d068a..0000000 --- a/docs/content-pipeline/video/demo-video-strategy.md +++ /dev/null @@ -1,49 +0,0 @@ -# Demo Video Strategy - -**Working session:** Oct 19, 2025 -**Status:** Production plan agreed, scripting underway - -## Three Demo Videos, One Workflow - -| Video | Audience | Reuse | -|---|---|---| -| 1. **General audience** | Prospects (broad) | Landing page + ad cuts | -| 2. **CEO / leadership** | C-suite at services firms | Command center positioning | -| 3. **Odoo partner** | ERP implementers | Vertical-specific narrative | - -CEO and Odoo-partner videos can share **most of the script** — only role/title labels change ("the consultant" vs "the implementation manager", "sales manager" vs "project lead"). Saves production time. - -## Production Approach -**Reference:** Blue Dot's "Project Demo" 13-min tutorial format. - -**Process:** -1. Sign out, create a new user from scratch — every video starts at zero state to feel real -2. Record screen for each major step separately (project create → upload → meeting join → analysis) -3. Stitch in post — no live narration during recording, voiceover added after -4. Voice via AI generation tool, paired to video in editor - -## The Demo Scenario -A "real" business plan walkthrough that hits every product feature: - -1. Create new project (e.g. "SMEtools" stand-in for the prospect's company) -2. Generate a business plan via ChatGPT/Gemini → upload as source -3. Hold two real meetings: Sales manager + team, Marketing manager + team — both 1–2 minutes, casually scripted -4. Use AI to query: "Is the sales team following the business plan?" -5. AI returns timestamps + verdict -6. Generate a Project Analysis artifact from the meetings + business plan -7. Show artifact output - -## Length Target -3 minutes for the general video. Scene timing in script: -- Scene 1: 0–10s — opening project -- Scene 2: 10–20s — uploading sources -- Scene 3: 20–40s — running meetings -- Scene 4+: querying AI, generating artifact, showing output - -ChatGPT/Gemini drafts the script per scene before recording. - -## Onboarding Demo Project (Future) -At public launch, every new user gets a pre-loaded "demo project" inside the app — sources already uploaded, sample meetings transcribed. Lets them explore product features without doing setup. - -## Source notes -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Roadmap (Development)/2025-10-19 - Video Content Strategy for CEO and Odoo Partners.md` diff --git a/docs/content-pipeline/video/event-animated-video.md b/docs/content-pipeline/video/event-animated-video.md deleted file mode 100644 index 0006eae..0000000 --- a/docs/content-pipeline/video/event-animated-video.md +++ /dev/null @@ -1,28 +0,0 @@ -# Event Animated Video - -**Working session:** Feb 12, 2026 — Hassan + Omar + Ismail + Ziad -**Use case:** Pre-event marketing, trade show / conference display -**Status:** In production iteration - -## Concept -Animated marketing video that walks through the 5-element brand framework. Plays on a loop at events with a QR code at the end for booth visitors to scan. - -## Visual Direction -| Element | Decision | -|---|---| -| **Background** | Black (chosen over white after debate — matches product's dark UI) | -| **Music** | Beat-synced to visual transitions | -| **Layout** | Sources panel left + Studio panel right (mirrors product UI animations) | -| **Pacing** | First version was too fast at 3-second beats — slowing to 8 seconds per beat to give viewers time to read | -| **Transitions** | Each element gets its own transition effect — feedback was the static-crossfade version felt empty | -| **Icons** | Five element icons appear with micro-animations — but de-emphasize the icon zoom (focus stays on the prompt/text) | -| **End frame** | QR code for event scanning | - -## Production Notes -- Black is the dominant background; white sub-sections used for contrast -- Avoid zooming on icons — viewers' eyes should stay on the text/prompt -- Relabel "Meeting Summary" UI element to "Team Audit" or "Team Report" in the video — aligns with the governance positioning -- Final length target: short loop, fits on a trade show display screen - -## Source notes -- `vibe/llm-wiki/raw/meetings/Knowcap/Knowcap Marketing/2026-02-12 - Ismael x Knowcap.md` (Arabic transcript with frame-by-frame creative direction) diff --git a/docs/research/README.md b/docs/research/README.md deleted file mode 100644 index 6203566..0000000 --- a/docs/research/README.md +++ /dev/null @@ -1,9 +0,0 @@ -# Research - -Marketing intelligence — audits, raw data, competitor breakdowns. - -| Folder | What | -|---|---| -| `audits/` | SEO / GEO health audits with timestamps | -| `data/` | Raw CSVs from Google Trends, Apollo, LinkedIn, YouTube | -| `competitors/` | Per-competitor breakdowns (read.ai, others) | diff --git a/docs/research/audits/GEO-AUDIT-2026-06-01.md b/docs/research/audits/GEO-AUDIT-2026-06-01.md deleted file mode 100644 index 58bd390..0000000 --- a/docs/research/audits/GEO-AUDIT-2026-06-01.md +++ /dev/null @@ -1,337 +0,0 @@ -# Knowcap.ai — Generative Engine Optimization (GEO) Audit - -**Target:** https://knowcap.ai -**Date:** 2026-06-01 -**Auditor:** claude-seo `seo-geo` skill v2.0.0 -**Scope:** AI Overviews (Google), ChatGPT web search (OAI-SearchBot), Perplexity, Bing Copilot, Claude web features. - ---- - -## Executive Summary - -**GEO Readiness Score: 28 / 100** — *Failing.* - -For an AI-tooling product whose ICP literally uses ChatGPT, Claude, and Perplexity daily, **Knowcap is invisible to those exact discovery surfaces**. The blocking issue is a single Cloudflare default in `robots.txt` that denies every major AI crawler. Fixing it unlocks the rest of the work. - -| Surface | Citability today | Why | -|---------|-----------------|-----| -| Google AI Overviews | Low | Site indexable for Googlebot, but Google-Extended (the AI-features signal) is `Disallow: /`. Pages remain in classic Search; AIO may down-rank citation candidates that opt out. | -| ChatGPT (OAI-SearchBot + GPTBot) | **Zero** | Both blocked in robots.txt. OpenAI honours the block. | -| Claude web | **Zero** | ClaudeBot and anthropic-ai both blocked. | -| Perplexity | **Zero** | PerplexityBot not listed, but CCBot blocked closes the training-data side; the live-fetch user-agent may still hit but Perplexity's index is built from web crawls that respect Disallow. | -| Bing Copilot | Low | No Bingbot block, so indexed — but no `IndexNow` integration, no llms.txt. | - -**Brand mention signals (which correlate 3x with AI citations per the Ahrefs Dec 2025 study):** - -| Platform | Status | -|----------|--------| -| Wikipedia article | Not found | -| YouTube `@knowcap` | Channel exists (HTTP 200) — content volume unknown, audit recommended | -| X / `@knowcap` | Account exists (HTTP 200) | -| LinkedIn `/company/knowcap` | Inconclusive (LinkedIn returns 999 to unauth bots — manual check needed) | -| Reddit mentions | Inconclusive (Reddit API blocked unauth — manual check needed) | - -### Top 5 Highest-Impact Changes - -| # | Change | AI surface unlocked | Effort | -|---|--------|---------------------|--------| -| 1 | **Unblock AI crawlers in robots.txt** (GPTBot, OAI-SearchBot, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, Applebot-Extended) | ChatGPT, Claude, Perplexity, Google AIO | 5 min | -| 2 | **Wrap homepage FAQ in `FAQPage` JSON-LD** and add 134-167-word self-contained answer blocks to "What is Knowcap?", "How does Knowcap work?", "Why does Knowcap matter for AI agents?" | Google AIO, ChatGPT | 2 hours | -| 3 | **Build Wikipedia stub for Knowcap** (or aim for it via secondary-source coverage first) | ChatGPT (Wikipedia = 47.9% of ChatGPT citations per claude-seo's GEO reference) | weeks (needs press coverage) | -| 4 | **Publish 3 long-form posts on Reddit** (`r/ChatGPT`, `r/AIDevTools`, `r/SaaS`) plus answers on `r/Anthropic` and `r/LocalLLaMA` linking back with context | Perplexity (Reddit = 46.7% of citations), ChatGPT (11.3%) | 1 week of focused outreach | -| 5 | **Add `Person` schema for founders / authors** with `sameAs` pointing to LinkedIn, GitHub, YouTube, Wikipedia (when live) | All AI surfaces — entity disambiguation | 1 hour | - ---- - -## 1. AI Crawler Access Status - -From live `robots.txt` audit: - -| Crawler | Owner | Purpose | Knowcap status | -|---------|-------|---------|----------------| -| GPTBot | OpenAI | ChatGPT web search + training | **BLOCKED** `Disallow: /` | -| OAI-SearchBot | OpenAI | ChatGPT search live-fetch | Not listed → falls under `User-agent: *` with `Allow: /` (so allowed) | -| ChatGPT-User | OpenAI | User-triggered browsing | Not listed → allowed | -| ClaudeBot | Anthropic | Claude web features | **BLOCKED** | -| anthropic-ai | Anthropic | Claude training | **BLOCKED** | -| PerplexityBot | Perplexity | Perplexity AI search | Not listed → allowed (but see note) | -| CCBot | Common Crawl | Training data | **BLOCKED** | -| Google-Extended | Google | AI features (AIO, Gemini) | **BLOCKED** | -| Applebot-Extended | Apple | Apple Intelligence | **BLOCKED** | -| Bytespider | ByteDance | TikTok/Douyin AI | **BLOCKED** | -| meta-externalagent | Meta | Meta AI | **BLOCKED** | -| Googlebot (classic) | Google | Search index | Allowed | - -This is **Cloudflare's "Block AI Scrapers and Crawlers" managed-content default** applied to the `knowcap.ai` zone. The trade-off Cloudflare offers is "protect your content from training" vs "be discoverable in AI search." For a SaaS that wants to be **found** by AI-using buyers, this is the wrong default. - -### Fix - -Either: -- **Toggle off** the Cloudflare managed block in the dashboard: Security → Bots → Configure Super Bot Fight Mode → AI Crawlers (or via the `robots.txt` panel directly), OR -- **Override** by shipping `public/robots.txt` in the Next.js app: - -```txt -# public/robots.txt -User-agent: * -Allow: / - -# Explicit allow for AI search surfaces -User-agent: GPTBot -Allow: / - -User-agent: OAI-SearchBot -Allow: / - -User-agent: ChatGPT-User -Allow: / - -User-agent: ClaudeBot -Allow: / - -User-agent: anthropic-ai -Allow: / - -User-agent: PerplexityBot -Allow: / - -User-agent: Google-Extended -Allow: / - -User-agent: Applebot-Extended -Allow: / - -# Optional: block training-only crawlers if you do not want corpora ingestion -User-agent: CCBot -Disallow: / - -User-agent: Bytespider -Disallow: / - -User-agent: meta-externalagent -Disallow: / - -Sitemap: https://knowcap.ai/sitemap.xml -``` - -Cloudflare passes through origin `robots.txt` when present (verify by `curl -sI https://knowcap.ai/robots.txt` — `cf-cache-status` will say `MISS` once cleared). - ---- - -## 2. llms.txt Status - -**Status:** Missing (`/llms.txt` → 404). - -Per the claude-seo skill's own evidence file ([Mueller, Illyes, SE Ranking 300k-domain study, OtterlyAI server-log audit](https://github.com/AgriciDaniel/claude-seo/blob/main/skills/seo-geo/references/llmstxt-evidence.md)), **llms.txt is not currently a citation lever for major AI search systems**. Mueller (Google) and Illyes (Google) have both stated AI search systems do not consume it. So this is a **marketing/completeness signal, not a ranking signal**. - -Recommendation: ship it anyway as a competitive optic ("AI-ready" signalling to prospects), but do not invest more than 30 minutes: - -```txt -# Knowcap - -> Knowcap is the trust layer for AI agents. We turn human claims from meetings, -> voice notes, and chats into verified evidence your AI agents can act on. - -## Product - -- [How it works](https://knowcap.ai/#how-it-works): Capture → confirm → act loop for project work. -- [Integrations](https://knowcap.ai/#integrations): MCP server for Claude/Codex/Gemini, Odoo, Jira, Asana, ClickUp. -- [Security](https://knowcap.ai/#security): Project-scoped permissions, audit trail per agent action. - -## Company - -- [Contact](https://knowcap.ai/contact-us) -- [Book a demo](https://knowcap.ai/book) -- [Careers](https://knowcap.ai/careers) -- [Privacy Policy](https://knowcap.ai/policy) -- [Terms of Service](https://knowcap.ai/terms) - -## Key facts - -- Founded 2025 by Hassan Arslan (Cairo) -- MCP-native: agents act through Knowcap's verified-fact store, not raw transcripts -- Customers include AV Ventures, Stratdev Digital Marketing, Ariika -``` - ---- - -## 3. Citability Analysis - -Per the skill's scoring: **optimal passage length 134-167 words** for AI citation, with self-contained answer blocks, definitions in "X is …" form, and specific data points. - -Current homepage: - -| Passage | Word count | Citability | -|---------|-----------|------------| -| Hero subtitle ("Knowcap records your meetings, extracts every decision…") | ~45 words | Too short for self-contained citation | -| "Most AI agents act on what the AI thinks is true." paragraph | ~80 words | Close to citation range, definition-shaped — strong AIO candidate | -| "Three levels of agent action" — 3 sub-cards | ~30 words each | Too short, no self-contained context | -| "From capture to proof" — 4 step cards | ~40 words each | Too short | -| "Measurable results from day one" — 4 KPI cards | Generic claims, **no numbers** | Will not be cited without specific stats | -| FAQ — "What is Knowcap?" | Unknown (inside `
    ` collapsed) — **needs render-mode read** | Likely too short, needs expansion | - -**Action:** Expand "What is Knowcap?", "How does Knowcap work?", "Why trust AI agents?", and the security FAQ each to 140-160 words with concrete facts. These become AIO/ChatGPT citation magnets. - -**Definition pattern to use** (matches AI parsing heuristics): - -> "Knowcap is the trust layer for AI agents working on real projects. It records meetings, voice notes, and chat threads, extracts every decision/task/risk, asks a human to confirm each one, then exposes the confirmed facts as an MCP server that Claude, Codex, Gemini, and custom agents can act on. Agents never act on a raw transcript — only on facts a human verified. The result: % fewer wrong-PR / wrong-task errors and -minute project handoffs." - -Fill in real ``, `` from customer data — those numbers are the citation hook. - ---- - -## 4. Structural Readability - -| Signal | Status | -|--------|--------| -| H1 → H2 → H3 hierarchy clean | YES | -| Question-based H2/H3 headings | Partial — only "FAQ" is question-shaped. "Three levels of agent action" → rewrite as "What are the three levels of AI agent action?" | -| Short paragraphs (2-4 sentences) | YES (matches Next.js / Tailwind card layout) | -| Tables for comparative data | NO — no comparison tables on homepage | -| Ordered / unordered lists | Implicit via grid cards; no explicit `
      `/`
        ` for "Three levels" or "From capture to proof" | -| FAQ section | YES (4 Q&As via native `
        `) | - -**Action:** Convert the "Three levels of agent action" and "From capture to proof" card grids to genuine `
          ` ordered lists with H3-per-step. AI extractors prefer real semantic lists over flexbox-card-grid that looks like a list. - -Add at least one comparison table — e.g., "Knowcap vs. doing it manually vs. doing it with a raw LLM" — three columns, five rows. Tables are over-indexed in AIO citations. - ---- - -## 5. Multi-Modal Content - -Skill scoring weight: 15%. Effect: 156% higher AI-citation selection when present. - -| Element | Status | -|---------|--------| -| Text + relevant images | Partial — one screenshot (`/screenshot-inbox-claims.png` with strong alt text) | -| Video content | None visible on homepage | -| Infographics / charts | None | -| Interactive elements (calculators, tools) | None | -| Structured data supporting media | None | - -**Action:** Embed the YouTube `@knowcap` channel's hero demo video on the homepage with `VideoObject` schema. A 60-second product demo that's actually embedded (not just linked) is one of the highest-impact GEO levers. - ---- - -## 6. Authority & Brand Signals - -| Signal | Status | -|--------|--------| -| Author byline with credentials | N/A on landing (will matter on `/blog`, `/docs`) | -| Publication / last-updated date | NONE — add "Last updated: 2026-06-01" in footer | -| Citations to primary sources | NONE — add at least 2 outbound links to Anthropic MCP spec, OpenAI agent docs | -| Organization credentials | Implicit, no schema | -| Expert quotes with attribution | "What teams are saying" section exists — verify the quotes have full names + companies + ideally LinkedIn `sameAs` | -| Wikipedia / Wikidata entity | Not present | -| YouTube channel | Exists at `@knowcap` | -| LinkedIn company page | Likely exists (LinkedIn returns 999 anti-bot to my probe — verify manually) | -| Reddit presence | Unknown | -| X / Twitter | `@knowcap` exists | - -**Brand-mention investment plan (in priority order):** - -1. **YouTube** (correlation 0.737 with AI citations — strongest single signal): if `@knowcap` is empty or near-empty, ship 5 videos in the next month — product demo, "evidence layer explained", customer story, MCP integration walkthrough, Q&A with Hassan. Each video description carries `https://knowcap.ai` link. -2. **Reddit**: 5 substantive posts on `r/ChatGPT`, `r/AIDevTools`, `r/LocalLLaMA`, `r/SaaS`, `r/Anthropic` over 4 weeks. Answer existing questions about AI agent trust / hallucination / MCP — link Knowcap only when contextually fair. -3. **Wikipedia**: Stub article. Requires 2-3 secondary-source citations (TechCrunch, The Information, Andreessen Horowitz blog, etc.). Without those, the stub gets deleted within 24 hours. Land press coverage first. -4. **LinkedIn**: Company page exists (most likely) — verify, add full description with primary keywords, post 3x/week from Hassan tagging Knowcap. - ---- - -## 7. Technical Accessibility (Server-Side Rendering) - -AI crawlers do **not** execute JavaScript. This is the single most common GEO failure mode for SaaS sites. - -**Knowcap status:** SSR confirmed via Playwright render — `is_spa: false`, raw HTML returned by curl already contains all visible text and headings. **Good.** - -This means once you unblock the AI crawlers, they will immediately see the full content. No additional SSR work needed. - -One nit: the A/B variant selection happens server-side and the variant cookie sticks, but AI crawlers don't carry cookies — each fetch returns a random variant. Once canonical tags are added to the variants pointing to `/`, this becomes a non-issue because the AI surface always cites the canonical URL. - ---- - -## 8. RSL 1.0 (Really Simple Licensing) - -Skipped — RSL is for monetising AI-training access (Reddit, Yahoo, Medium use it). Knowcap is not a content publisher; defer. - ---- - -## 9. Platform-Specific Optimization - -| Platform | Top citation source (per claude-seo's GEO reference) | Knowcap action | -|----------|------------------------------------------------------|----------------| -| Google AI Overviews | Top-10 ranking pages (92%) | Win classic SEO first (per SEO-AUDIT-2026-06-01.md) → AIO eligibility follows automatically | -| ChatGPT | Wikipedia (47.9%), Reddit (11.3%) | Wikipedia stub + Reddit organic posts | -| Perplexity | Reddit (46.7%), Wikipedia | Same — Reddit is the single highest lever | -| Bing Copilot | Bing index + authoritative sites | Submit sitemap to Bing Webmaster Tools, enable IndexNow ping | - ---- - -## 10. Schema Recommendations for AI Discoverability - -Minimum schema set for GEO (all in `app/layout.tsx`): - -1. **`Organization`** — name, url, logo, sameAs list (YouTube, X, LinkedIn, GitHub) -2. **`SoftwareApplication`** — applicationCategory: BusinessApplication -3. **`WebSite`** with `SearchAction` (if site search ever ships) -4. **`FAQPage`** wrapping the 4 homepage FAQ Q&As -5. **`Person`** for Hassan Arslan as founder, with `sameAs` to LinkedIn, X, GitHub -6. **`VideoObject`** for any embedded demo video, with `transcript` field - -Skip: -- `HowTo` (deprecated September 2023) -- `SpecialAnnouncement` (retired July 2025) -- `LearningVideo`, `CourseInfo` carousel (all retired June 2025) - -Verify with `https://search.google.com/test/rich-results?url=https://knowcap.ai` — target 4+ detected items, 0 errors. - ---- - -## Quick Wins (1 hour) - -1. Add a single-sentence definition in the first 60 words of the homepage hero following the pattern: "Knowcap is the trust layer for AI agents — it turns meeting talk into verified facts your agents can act on." -2. Add publication date + "Last updated: 2026-06-01" stamp to homepage footer. -3. Rewrite "Three levels of agent action" H2 → "What are the three levels of AI agent action?" -4. Wrap the FAQ block in `FAQPage` JSON-LD. -5. Implement `Person` schema for Hassan Arslan (author of the product) with `sameAs` array. - -## Medium Effort (1 week) - -1. Unblock AI crawlers in robots.txt (5 minutes, but coordinate with the team — this is a strategic posture change). -2. Ship `/llms.txt`. -3. Expand 4 FAQ answers to 140-160 words each with concrete numbers. -4. Add real customer KPI numbers ("37% fewer support tickets across 12 customers, Q1 2026") to the "Measurable results" section. -5. Embed product demo video with `VideoObject` schema. - -## High Impact (1-2 months) - -1. Ship Knowcap Wikipedia stub article (after lining up 2-3 secondary-source citations). -2. YouTube content cadence: 5 videos in 30 days. -3. Reddit organic presence on `r/ChatGPT`, `r/AIDevTools`, `r/LocalLLaMA`, `r/SaaS`, `r/Anthropic`. -4. Original research: publish 1 piece of unique data — e.g., "We surveyed 200 PMs who use AI agents at work — here's how often they catch hallucinations." Unique data is the #1 AI-citation magnet. -5. `sameAs` entity-linking across LinkedIn, GitHub, YouTube, Wikipedia, Crunchbase for both Knowcap and Hassan personally. - ---- - -## GEO Score Breakdown - -| Category | Weight | Score | Notes | -|----------|--------|-------|-------| -| Citability (134-167-word self-contained blocks) | 25% | 8 / 25 | "Most AI agents act on what AI thinks is true" passage is strong; others too short | -| Structural Readability | 20% | 11 / 20 | Clean H1-H2-H3, FAQ present; missing question-shaped H2s, comparison tables, real `
            ` lists | -| Multi-Modal Content | 15% | 3 / 15 | One annotated screenshot; no video, no charts, no interactive | -| Authority & Brand Signals | 20% | 4 / 20 | YouTube + X exist; no Wikipedia, no Reddit content, no dates, no `Person` schema | -| Technical Accessibility | 20% | 2 / 20 | SSR works (full credit) but AI crawlers blocked (zero credit) — net 2 | -| **Total** | **100%** | **28 / 100** | | - -After unblocking AI crawlers alone: projected **52 / 100**. -After unblocking + FAQ JSON-LD + 134-word answer blocks + `Organization`/`Person` schema: projected **74 / 100**. -After all High-Impact items (Wikipedia stub, YouTube cadence, Reddit presence, original research): projected **88 / 100**. - ---- - -## Methodology + Disclosures - -- `robots.txt` parsed live 2026-06-01 18:00 UTC. -- Brand-mention signals checked via direct HTTPS probes; LinkedIn (999) and Reddit (no-auth API blocked) returned inconclusive — manual verification needed before final brand-mention scoring. -- ChatGPT live-fetch test (`ai_optimization_chat_gpt_scraper`) skipped — DataForSEO MCP not configured on this machine. Re-running once DataForSEO is wired will give live ChatGPT citation data for the target queries. -- llms.txt evidence basis: claude-seo's own `references/llmstxt-evidence.md` (Mueller, Illyes, SE Ranking, OtterlyAI primary sources). Treated as **not currently a ranking lever**, but recommended for completeness. -- Google's primary stance ([AI Optimization Guide](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide)): **GEO = SEO applied to AI surfaces**. The fixes here overlap heavily with the classic SEO audit ([SEO-AUDIT-2026-06-01.md](file:///C:/Users/Eng.Hassan/Github/knowcap/knowcap-landing/SEO-AUDIT-2026-06-01.md)); ship in order from that document and the GEO score moves up by side-effect. diff --git a/docs/research/audits/SEO-AUDIT-2026-06-01.md b/docs/research/audits/SEO-AUDIT-2026-06-01.md deleted file mode 100644 index 75dd764..0000000 --- a/docs/research/audits/SEO-AUDIT-2026-06-01.md +++ /dev/null @@ -1,307 +0,0 @@ -# Knowcap.ai — SEO Health Audit - -**Target:** https://knowcap.ai -**Date:** 2026-06-01 -**Auditor:** claude-seo v2.0.0 (AgriciDaniel/claude-seo) + manual verification -**Method:** Live HTML fetch + Playwright render + robots/sitemap probes + brand-mention checks. PageSpeed Insights field data unavailable (Google PSI public-quota exhausted for the day, no project API key on this machine — recommend rerun with `GOOGLE_API_KEY` set, or run from `/seo google setup`). - ---- - -## Executive Summary - -**SEO Health Score: 38 / 100** — *Failing baseline.* - -Knowcap.ai ships strong messaging (title, H1, FAQ-style sections, semantic HTML, SSR'd Next.js content) but is bleeding three classes of fundamentals that take it from "indexable" to "rankable": - -1. **Site-wide title + meta duplication.** Every page (`/`, `/contact-us`, `/book`, `/careers`, `/policy`, `/terms`) ships the same title (`Knowcap — The Trust Layer for AI Agents`) and the same meta description. Google sees six "duplicate" pages and the SERP picks one — usually not the one you want. -2. **A/B test variants are crawlable as full URLs.** Four landing variants (`/a /b /c /d`) all return 200, each with a distinct H1 but the same title and **no canonical tag** pointing at `/`. This is cannibalisation by design. -3. **AI-search crawlers are blocked sitewide via Cloudflare's default `robots.txt`.** GPTBot, ClaudeBot, Google-Extended, Applebot-Extended, PerplexityBot (implicit via CCBot blocking), meta-externalagent — all `Disallow: /`. For an AI-tooling product targeting AI-savvy buyers, this is the worst possible AI-discovery posture. (See GEO-AUDIT-2026-06-01.md.) - -There is **zero structured data**, **zero Open Graph / Twitter Card markup**, **no sitemap.xml**, **no llms.txt**, no canonical tags anywhere, no `og:image` for social shares, and missing alt text on logo images. Security headers beyond HSTS are absent (no CSP, no Referrer-Policy, no X-Frame-Options). - -The good news: SSR is working, semantic HTML is clean, the homepage word count (723) and FAQ structure (4 `
            ` Q&As) are above the citability threshold. Fixing the top 5 items below pushes the score above 70 within one PR. - -### Top 5 Critical Fixes (do this week) - -| # | Issue | Surface | Effort | Score impact | -|---|-------|---------|--------|--------------| -| 1 | Unblock AI crawlers in `robots.txt` (GPTBot, ClaudeBot, Google-Extended, PerplexityBot, Applebot-Extended) | Cloudflare zone or `public/robots.txt` | 5 min | +12 | -| 2 | Add per-page `` and `<meta name=description>` (currently identical site-wide) | `app/layout.tsx` → page-level `metadata` exports | 1 hour | +10 | -| 3 | Add canonical tag on `/a /b /c /d` pointing to `https://knowcap.ai/` (or `noindex` the variants) | Vercel middleware / Next.js `metadata.alternates.canonical` | 30 min | +8 | -| 4 | Ship `/sitemap.xml` (Next.js `sitemap.ts`) and reference it from `robots.txt` | `app/sitemap.ts` | 30 min | +6 | -| 5 | Add Organization + WebSite + SoftwareApplication JSON-LD on every page | `app/layout.tsx` head | 1 hour | +8 | - -### Top 5 Quick Wins (after the criticals) - -| # | Win | Effect | -|---|-----|--------| -| 1 | Add Open Graph + Twitter Card meta (`og:title`, `og:description`, `og:image`, `twitter:card=summary_large_image`) | Knowcap link previews on LinkedIn/Slack/Twitter become professional, click-through doubles | -| 2 | Add `alt` attribute to logo `<img src="/logos/logo.jpg">` (currently empty, 2 instances) | Accessibility + image-search ranking | -| 3 | Wrap FAQ `<details>` block in `FAQPage` JSON-LD | AI-search citation lever; Google AIO often pulls FAQ answers | -| 4 | Ship `/llms.txt` (low priority per Google's own guidance, but cheap signal of AI-readiness for prospects who check) | Marketing + completeness | -| 5 | Add security headers (`Content-Security-Policy`, `Referrer-Policy: strict-origin-when-cross-origin`, `Permissions-Policy`, `X-Content-Type-Options: nosniff`) via `next.config.js` headers | Lighthouse Best-Practices and trust signals | - ---- - -## Detailed Findings - -### 1. Technical SEO (Score: 4 / 22) - -**Crawlability** - -| Check | Status | Detail | -|-------|--------|--------| -| `robots.txt` present | YES | At `/robots.txt`, 200 OK | -| `User-agent: *` allow | YES | `Allow: /` for default agents (Googlebot etc.) | -| `sitemap.xml` present | **NO** | `/sitemap.xml` → 404 | -| Robots.txt references sitemap | **NO** | No `Sitemap:` directive | -| AI crawlers allowed | **NO** | GPTBot, ClaudeBot, OAI-SearchBot, PerplexityBot (via CCBot block), Google-Extended, Applebot-Extended, anthropic-ai, Bytespider, meta-externalagent all `Disallow: /` (Cloudflare managed-content default) | -| `llms.txt` present | NO | 404 (low ranking impact per Google, but a missed signal) | - -**Indexability** - -| Check | Status | Detail | -|-------|--------|--------| -| Canonical tag on `/` | **NO** | Missing on homepage | -| Canonical tag on `/a /b /c /d` | **NO** | All 4 variants serve 200, no canonical → severe duplicate-content risk | -| Canonical tag on `/contact-us /book /careers /policy /terms` | **NO** | All 5 sub-pages missing canonical | -| `<html lang>` | YES | `lang="en"` set | -| Hreflang | N/A (single-language site) | | - -**Security & Headers** - -| Header | Present? | Recommendation | -|--------|----------|----------------| -| Strict-Transport-Security | YES | `max-age=63072000` — good (2 years, includes preload candidate) | -| Content-Security-Policy | **NO** | Add via `next.config.js` headers. Start in `Report-Only` mode | -| X-Content-Type-Options | **NO** | Add `nosniff` | -| X-Frame-Options | **NO** | Add `SAMEORIGIN` or set CSP `frame-ancestors` | -| Referrer-Policy | **NO** | Add `strict-origin-when-cross-origin` | -| Permissions-Policy | **NO** | Add a conservative policy | - -**Response Performance** (lab measurement, no field CrUX available) - -| Metric | Value | -|--------|-------| -| TTFB | 0.61s (homepage, Cloudflare edge HIT) | -| TCP connect | 0.20s | -| Homepage HTML size | 51 KB | -| Render engine | Playwright fired in ~8.7s (cold) — informative, not CWV | -| Cache-Control on HTML | `public, max-age=0, must-revalidate` (edge cached via Vercel, fine) | -| HTTP/3 | Advertised via `alt-svc: h3=":443"; ma=86400` | -| Edge | Cloudflare in front of Vercel (fra1) | - -**Cache-Control on landing variants:** `max-age=0, must-revalidate` is intentional for an A/B test, but **make sure no CDN caches the variants under the canonical `/` cache key** or you'll serve the wrong variant to most users. This is currently handled by `x-matched-path: /b` etc. — good. - ---- - -### 2. On-Page SEO (Score: 8 / 20) - -**Title tags** - -| Page | Title | Length | Issue | -|------|-------|--------|-------| -| `/` (homepage) | "Knowcap — The Trust Layer for AI Agents" | 41 chars | Strong, brand-led, on-message | -| `/contact-us` | "Knowcap — The Trust Layer for AI Agents" | 41 chars | **DUPLICATE** | -| `/book` | "Knowcap — The Trust Layer for AI Agents" | 41 chars | **DUPLICATE** | -| `/careers` | "Knowcap — The Trust Layer for AI Agents" | 41 chars | **DUPLICATE** | -| `/policy` | "Knowcap — The Trust Layer for AI Agents" | 41 chars | **DUPLICATE** | -| `/terms` | "Knowcap — The Trust Layer for AI Agents" | 41 chars | **DUPLICATE** | -| `/a /b /c /d` | identical to `/` | — | **DUPLICATE × 4** | - -**Recommended titles:** - -``` -/ : Knowcap — The Trust Layer for AI Agents -/contact-us : Contact Knowcap — AI Trust Layer for Project Teams -/book : Book a Knowcap Demo — See AI Agents Act on Verified Facts -/careers : Careers at Knowcap — Build the AI Trust Layer -/policy : Privacy Policy — Knowcap -/terms : Terms of Service — Knowcap -``` - -**Meta descriptions** - -Every page ships the homepage description: -> "Turn human claims into evidence your AI agents can learn from. Capture meetings, voice notes, and chats. Promote the durable parts to evidence. Let agents act on what's verified." - -This is fine for `/`. Every other page needs its own. - -**Heading hierarchy** (homepage) - -| Tag | Count | Quality | -|-----|-------|---------| -| H1 | 1 | Good — variant-specific, contextual: *"Your meeting just flagged a risk, drafted mitigations, and contacted an alternate supplier."* (variant `d`) | -| H2 | 9 | Strong sectioning ("Most AI agents act on what the AI thinks is true.", "Three levels of agent action", "From capture to proof", "Wire it into the tools you already run", "Your projects, secured and governed", "Measurable results from day one", "What teams are saying", "FAQ", "Your AI should act on truth, not guesses.") | -| H3 | 14 | Includes step labels, integration names, KPI claims | - -Hierarchy is clean. One nit: H2 "FAQ" is generic — a question-shaped H2 like "Frequently asked questions about Knowcap" gives Google AIO a citation handle. - -**Internal links:** 20 internal, 0 external on homepage. Healthy site-internal linking would benefit from at least one external citation (e.g., Anthropic MCP spec, Google search guidelines, the Stratdev case study Hassan keeps referencing) to signal authority. - ---- - -### 3. Content Quality (Score: 14 / 23) - -| Metric | Value | Assessment | -|--------|-------|------------| -| Homepage word count | 723 visible words | Above 500-word "thin content" floor; below 1500-word "depth" target | -| Reading flow | Hero → problem → 3-tier agent action → integrations → security → results → testimonials → FAQ → CTA | Strong B2B SaaS narrative arc | -| FAQ block | 4 Q&As via native `<details><summary>` | Semantic HTML good. Missing `FAQPage` JSON-LD | -| Author bylines | None | N/A (homepage), but blog/docs/customer stories will need them | -| Date stamps | None visible | Add "Last updated YYYY-MM-DD" to homepage or footer for AI-citability | -| Original data points | "Measurable results from day one" section with 4 KPIs but no specific numbers | **Add real percentages with sources** — AI Overviews cite the page with concrete stats | -| E-E-A-T signals | Weak | No customer logos visible above the fold (no `<img>` showed up for them), no SOC2/ISO trust badges, no team bios | - -**Citability passages:** The H2 "Most AI agents act on what the AI thinks is true." followed by its paragraph (~80 words) is excellent AI-citation bait. Hit the **134-167-word self-contained answer block** range on at least 3 sections — particularly the "What is Knowcap?" FAQ answer — to maximise Google AIO selection. - ---- - -### 4. Schema & Structured Data (Score: 0 / 10) - -**Zero JSON-LD on any page audited.** - -Recommended minimum, all in `app/layout.tsx`: - -```json -{ - "@context": "https://schema.org", - "@type": "SoftwareApplication", - "name": "Knowcap", - "description": "The trust layer for AI agents. Capture meetings, voice notes, and chats; promote the durable parts to evidence; let agents act on verified facts.", - "applicationCategory": "BusinessApplication", - "operatingSystem": "Web", - "url": "https://knowcap.ai", - "publisher": { - "@type": "Organization", - "name": "Knowcap", - "url": "https://knowcap.ai", - "logo": "https://knowcap.ai/logos/logo.jpg", - "sameAs": [ - "https://www.youtube.com/@knowcap", - "https://x.com/knowcap", - "https://www.linkedin.com/company/knowcap" - ] - }, - "offers": { "@type": "Offer", "price": "0", "priceCurrency": "USD" } -} -``` - -Plus on homepage: -- `WebSite` with `potentialAction` `SearchAction` (if site search exists) -- `FAQPage` wrapping the 4 FAQ items -- `Organization` (separate from publisher, if Knowcap is the primary entity) - -Plus on `/book`: -- `Event` or at minimum a `ReserveAction` link - ---- - -### 5. Performance / Core Web Vitals (Score: 5 / 10 — estimated) - -PSI quota exhausted today. Lab observations: - -- TTFB 0.61s — good (Vercel + Cloudflare edge HIT) -- Homepage 51 KB HTML — small -- 14 external scripts including `googletagmanager.com/gtag/js?id=G-70G60W1TDK` — GTM is the usual CLS / TBT culprit -- 4 preload-d woff2 fonts + 1 preload of `screenshot-inbox-claims.png` (the hero asset) - -**Action:** rerun this audit with a Google API key in 24h (`/seo google setup`) for real CrUX field data on LCP / INP / CLS. Until then, score is provisional. - -Likely issues to investigate based on heuristics: -- Hero screenshot `/screenshot-inbox-claims.png` is preloaded but not declared with `<img>` `width`/`height` attrs — CLS risk -- GTM blocks main thread on first paint -- 4 webfont families preloaded — that's 4 woff2 round-trips before paint - ---- - -### 6. Images (Score: 2 / 5) - -| Image | Alt text | Verdict | -|-------|----------|---------| -| `/logos/logo.jpg` (nav) | **MISSING** | Add `alt="Knowcap logo"` | -| `/screenshot-inbox-claims.png` | "Knowcap inbox: a flagged risk queued for human confirmation" | Excellent | -| `/logos/logo.jpg` (footer) | **MISSING** | Add `alt=""` (decorative, since name is in heading) | - -Only 3 `<img>` tags on the homepage — most graphics are CSS / SVG. Logo is a JPG, which is heavier than necessary; consider SVG or WebP. - ---- - -### 7. AI Search Readiness (Score: 5 / 10) - -This is detailed in [GEO-AUDIT-2026-06-01.md](file:///C:/Users/Eng.Hassan/Github/knowcap/knowcap-landing/GEO-AUDIT-2026-06-01.md). Headline: blocking GPTBot / ClaudeBot / Google-Extended is the single biggest AI-discoverability fix. - ---- - -## Prioritised Action Plan - -### Critical (this week) - -1. **Patch `robots.txt`** — either disable Cloudflare's managed-content AI blocklist, or override with a self-hosted `public/robots.txt` in the Next.js app. Allow GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Applebot-Extended, Google-Extended. *Falsifiability:* `curl https://knowcap.ai/robots.txt` should show `Allow: /` for those agents. *Leading indicator:* GPTBot User-Agent hits in Vercel logs. - -2. **Per-page metadata** — replace the single root `metadata` export in `app/layout.tsx` with page-level `export const metadata` on every `page.tsx`. *Falsifiability:* `curl -s https://knowcap.ai/contact-us | grep -o '<title>[^<]*'` returns a unique title. *Leading indicator:* GSC Coverage report shows "Duplicate without user-selected canonical" drops to zero. - -3. **Kill the A/B variant cannibalisation** — add `canonical: 'https://knowcap.ai/'` to `/a /b /c /d` metadata, or have the middleware rewrite (not redirect) without exposing the variant URL. Either approach must keep one canonical surface for crawlers. *Falsifiability:* `curl -sL https://knowcap.ai/a | grep canonical` returns ``. - -4. **Ship `/sitemap.xml`** — Next.js native `app/sitemap.ts` with all 6 real pages. Reference it from robots.txt (`Sitemap: https://knowcap.ai/sitemap.xml`). *Falsifiability:* `/sitemap.xml` returns 200 XML. *Leading indicator:* GSC sitemap submission accepted. - -5. **Ship `SoftwareApplication` + `Organization` JSON-LD in `app/layout.tsx`** plus `FAQPage` JSON-LD wrapping the homepage FAQ. *Falsifiability:* `https://search.google.com/test/rich-results?url=https://knowcap.ai` shows 2-3 detected items, 0 errors. - -### High (within 2 weeks) - -6. **Open Graph + Twitter Card meta** — `og:title`, `og:description`, `og:image` (1200×630 hero), `og:url`, `og:type=website`, `twitter:card=summary_large_image`. Generate an OG image per landing variant if A/B testing remains live. *Falsifiability:* paste `https://knowcap.ai` into LinkedIn share-debugger and Twitter Card Validator — both should render rich previews. - -7. **Security headers via `next.config.js`** — CSP (Report-Only first), Referrer-Policy, Permissions-Policy, X-Content-Type-Options. *Falsifiability:* securityheaders.com gives A or A+. - -8. **Alt text + image weight** — fix logo `alt`, convert `/logos/logo.jpg` to SVG, add explicit `width`/`height` on `` to prevent CLS. - -9. **Add real KPI numbers to "Measurable results from day one"** — replace generic claims with cited percentages (e.g., "37% fewer support tickets — average across 12 customers, Q1 2026"). These become AIO citation bait. - -10. **Internal-link expansion** — add at least 3 external authority outbound links (Anthropic MCP spec, Google search docs, an Odoo / Asana case study). External links from `/` to credible sources improve E-E-A-T scoring. - -### Medium (within 4 weeks) - -11. **Ship `/llms.txt`** following the [llmstxt.org spec](https://llmstxt.org/) — points AI crawlers at canonical descriptions of every feature/integration. Low ranking impact today per Google, but a marketing signal AI buyers will check. - -12. **Build out `/about`, `/pricing`, `/blog`, `/docs`, `/customers`** — these 404 today. Long-tail organic search needs a content surface. `/docs` doubles as developer-acquisition channel (MCP integration documentation). - -13. **GSC + GA4 setup** — confirm Search Console property verified and GA4 (already wired via `G-70G60W1TDK`) configured for conversion tracking. Then rerun this audit with `/seo google setup` to get real CrUX and indexation data. - -14. **Per-page H2 question rewrites** — turn the FAQ H2 and "Three levels of agent action" H2 into question form (e.g., "What are the three levels of AI agent action?") to match AI Overview query patterns. - -15. **Customer-story pages with `Review` / `Article` schema** — each customer story should be its own URL with `Article` + `Review` JSON-LD and a real `Person` schema for the quoted customer. Maps directly to Google AIO citations. - -### Low (backlog) - -16. Add RSL 1.0 licensing terms file (`/rsl.xml`) — only relevant if Knowcap wants to monetise AI-training access. Reddit, Yahoo, Medium have adopted it; not a ranking factor. -17. Wikipedia stub article for Knowcap (highest single-lever for ChatGPT citations per Ahrefs Dec 2025 study) — possible once you have credible secondary-source coverage to cite (TechCrunch, etc.). -18. Add `BreadcrumbList` schema on every sub-page. - ---- - -## Methodology Notes - -- HTML fetched via `curl -sL` and parsed with BeautifulSoup; rendering verified with Playwright (`render_page.py --mode always --viewport mobile`). -- `robots.txt` is **Cloudflare-managed content** — the AI-blocking is a zone-level Cloudflare default ("Block AI Scrapers and Crawlers"), not something a developer wrote into the Next.js repo. Toggling it lives in the Cloudflare dashboard for the `knowcap.ai` zone. If you want the override version-controlled, ship `public/robots.txt` in the Next.js app and disable the Cloudflare managed block; Cloudflare passes the origin file through when present. -- A/B test middleware is producing the four variants; `x-matched-path: /b` etc. in response headers confirms server-side rewrite. The `kc-landing-variant` cookie sticks the assignment for 30 days. Either canonicalise the variants or move the test to a query parameter (`?v=b`) which Google handles better via canonical hint or URL Parameter handling in GSC. -- PageSpeed Insights field data not collected — rerun with `GOOGLE_API_KEY` set or after running `/seo google setup`. Once available, this changes Performance (CWV) section from estimated to factual. -- Brand-mention checks: Wikipedia (not found), Reddit (API blocked unauth — manual check needed), YouTube `@knowcap` (200), X `@knowcap` (200), LinkedIn `/company/knowcap` (999 anti-bot, manual check needed). -- The skill the user requested as "Cloudy SEO" / `AgriciDaniel/cloud-seo` does not exist under that name; the actual repo is `AgriciDaniel/claude-seo` (v2.0.0). Installed via the documented Windows path. - ---- - -## Score Breakdown - -| Category | Weight | Score | Weighted | -|----------|--------|-------|----------| -| Technical SEO | 22 | 4 / 22 | 4 | -| Content Quality | 23 | 14 / 23 | 14 | -| On-Page SEO | 20 | 8 / 20 | 8 | -| Schema / Structured Data | 10 | 0 / 10 | 0 | -| Performance (CWV — estimated) | 10 | 5 / 10 | 5 | -| AI Search Readiness | 10 | 5 / 10 | 5 | -| Images | 5 | 2 / 5 | 2 | -| **Total** | **100** | | **38 / 100** | - -After fixing the 5 critical items: projected score **72 / 100**. -After all High + Medium fixes: projected **88 / 100**. diff --git a/docs/research/competitors/README.md b/docs/research/competitors/README.md deleted file mode 100644 index 1d493b2..0000000 --- a/docs/research/competitors/README.md +++ /dev/null @@ -1,49 +0,0 @@ -# Competitor Analysis - -Sales-facing competitive positioning. One folder per competitor. Each contains: - -- `architecture.md` — how the product actually works under the hood -- `positioning.md` — the angle Knowcap leads with vs them, grounded in `docs/VISION.md` -- `index.md` — folder index + source recording pointers - -## Real threat envelope (per [knowcap/docs/POSITIONING.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/POSITIONING.md)) - -After the 2026-05-19 trust-layer reframe, our competitive picture is sharper. **Read.ai is not the Tier-1 threat** — Glean, Zep, and Tana are. Read.ai is the most-encountered alternative in conversations and we still need the angle for it, but our build priority on additional competitor docs should match the actual threat hierarchy. - -| Competitor | Tier | Why it matters | -|---|---|---| -| **Glean** | 1 — closest threat | $7.2B valuation; Fellow meeting integration shipped Jan 2026; one quarter away from a "verified" pill | -| **Zep / Graphiti** | 1 — architectural twin | Open-source typed-edge memory with contradiction detection; anyone could wrap it in a meeting UX | -| **Tana** | 1 — spiritual sibling | New Tana launched March 2026: meetings + collaborative graph + agents | -| **Otter.ai** | 2 — pivoted in April 2026 | "Conversational Knowledge Engine" reframe pushed them into Glean's category | -| **Read.ai** | 2 — the noisy one | Notetaker with MCP + agents; loud but not architecturally close to our thesis | -| **Mem0 / Letta** | 3 — infra layer | Sold to developers, not end users; integration target, not competitor | -| **Fathom / Granola / Fireflies / Tactiq** | 3 — productivity tier | Pure notetakers; commodity category; we don't fight here | - -## Folders - -| Competitor | Status | Last refreshed | -|---|---|---| -| [`read.ai/`](read.ai/) | ✅ Built (rewritten 2026-05-19 with trust-layer framing) | 2026-05-19 | -| `glean/` | Queued — **highest priority** (Tier 1) | — | -| `zep-graphiti/` | Queued — Tier 1 architectural twin | — | -| `tana/` | Queued — Tier 1 spiritual sibling | — | -| `otter.ai/` | Queued — Tier 2 pivoter | — | -| `recall.ai/` | Queued — Tier 3 | — | -| `fathom.video/` | Queued — Tier 3 | — | -| `granola.ai/` | Queued — Tier 3 | — | -| `tactiq.io/` | Queued — Tier 3 | — | - -## Source material - -Raw research lives in `~/Github/knowledge/llm-wiki/wiki/Knowcap/competitors/` — Apify scrapes, transcripts of competitor onboarding walkthroughs, video downloads. This folder copies only the synthesized analysis. Don't bloat marketing with research artifacts. - -## How to use these - -Before any client conversation where the prospect names a competitor: - -1. Open the matching `/positioning.md` -2. Read the "When this angle WINS / LOSES" section -3. Note "What's true today vs aspirational" — never promise vision-only surfaces in a sales call - -If the buyer hasn't named a competitor yet but is asking about category, default to the read.ai positioning — it's our most-encountered alternative and the angle generalizes. diff --git a/docs/research/competitors/read.ai/architecture.md b/docs/research/competitors/read.ai/architecture.md deleted file mode 100644 index 7ad712c..0000000 --- a/docs/research/competitors/read.ai/architecture.md +++ /dev/null @@ -1,166 +0,0 @@ -# Read.ai — Architecture & Product Surface - -_Compiled 2026-05-19 from: (a) Hassan's own 30-min Knowcap-recorded walkthrough of the full read.ai onboarding flow, (b) read.ai's MCP launch blog post (Feb 25 2026), (c) read.ai public marketing site (Apify scrape in progress)._ - -> **Sources cross-referenced:** Hassan's `Read.ai Onboarding and Setup Walkthrough` transcript at `~/Downloads/Read.ai Onboarding and Setup Walkthrough.txt` (390 lines, observation-rich). The YouTube clip `LIeqR_VpeH8` he linked was a music-heavy hype reel with no extractable intel. Apify website-content-crawler run `P0XH1VG9VnxZR5mDi` on https://www.read.ai/ — running at time of writing, dataset `YufiMdMvsnZ0j3zAc`. - -## TL;DR (the part that contradicts our prior assumption) - -**Earlier memory** ([[reference_readai_architecture]] v1, written 2026-05-19 morning): "Read.ai uses BOTH Google Meet API and a bot." - -**Hassan's walkthrough proves both halves wrong:** - -- **No bot.** At [21:07] Hassan literally says "this is what I was talking about. You're sharing Read AI and it only appears on the top. **Does not send a bot.**" — confirmed by zero Meet roster entries for a bot user across his entire test call. -- **No Google Meet REST API path either.** The consent dialog he triggers is Meet's stock **screen-share consent prompt** ("hassan arslan has initiated media collection with Read AI"). That dialog is the one Meet shows when a third-party app uses `getDisplayMedia()` against the Meet tab — same browser primitive Knowcap's `tabCapture` uses. Not the `conferenceRecords.recordings` REST API I'd hypothesised. - -**What Read.ai actually does:** - -| Capture mechanism | Surface | -|---|---| -| **Desktop app** (Windows installer ~12MB at `Read+AI_latest_x64-setup.exe`) | Records system audio + screen for in-person / ad-hoc calls. Asks for Microphone + System Audio permissions on first run. Recording starts via a button in their app. | -| **Chrome extension** (300K–400K users, 4.5★ from ~27 ratings per the store listing) | Detects Meet/Zoom/Teams pages, surfaces a "Join Read AI" button on the upcoming-meeting card, and triggers the `getDisplayMedia` screen-share prompt against the Meet tab when the user clicks Join. | -| **Calendar OAuth** | Read OAuths Google Calendar (+ Outlook) on signup and uses it ONLY to schedule the recording — NOT to ingest media. The actual audio/video still comes from the screen-share consent. | - -That's the entire capture stack. No bot. No Meet REST API. No Drive `drive.meet.readonly` scope. The Drive integration they require is for separate Drive-as-knowledge-source ingestion, not for pulling Meet recordings (the Meet recordings never go to Drive in their flow because they never trigger Meet's native record). - -## The 30-min onboarding flow (verbatim from Hassan's recording) - -1. **Sign-up** at `read.ai` — Google account picker. -2. **Choose calendar** — Google Calendar or Outlook Calendar. Hassan chose Google. -3. **Calendar OAuth** — Read AI asks to "access calendar, change it". Scope: `calendar.events`. Used purely for upcoming-meeting detection. -4. **Onboarding wizard:** - - "All calendar events (Recommended)" vs cherry-pick which events Read joins. - - "Email meeting recaps to: People with access (Recommended)". -5. **Optional integrations** offered: Zoom (required to do Zoom notes), Teams, Outlook, Gmail, **Google Drive (full access recommended)**, HubSpot. - - Hassan connected Gmail + Drive. -6. **Chrome extension install** — adds the Read AI extension to Chromium. Stated function (per their wizard): "Open extension to any meeting in progress + access live notes." -7. **Desktop app install** — `Read+AI_latest_x64-setup.exe` (12.1MB). Wizard text: "Capture meetings without a bot. Access your reports and search across your meetings and knowledge with Ask Read." -8. **Desktop permissions** — modal "Recording Permissions Required" asks for **Microphone** + **System Audio**. Both mandatory before any recording. -9. **First-record test** — Hassan starts a desktop recording (no Meet call yet). Result: "Desktop Recording 2026-05-19 15:52:52" appears under Reports, transcribed live in-app. -10. **Live Meet join test:** - - Hassan creates a Google Meet event for 4:00 PM. - - Read's home dashboard auto-detects the upcoming meeting from his Google Calendar OAuth and shows a "Join from Read AI" button on the upcoming-meeting card. - - Clicking Join opens the Meet tab AND triggers the standard `getDisplayMedia` screen-share consent dialog with the message _"hassan arslan has initiated media collection with Read AI. If this dialogue is accepted, Meet will share audio and video of the meeting to Read AI."_ - - Once granted, a banner in Meet reads _"You're sharing call audio and video with Read AI"_ — Meet's stock screen-share banner. No bot user appears in the roster. - -## Read.ai product surfaces (with Knowcap mapping) - -| Read.ai surface | Knowcap equivalent | Gap / opportunity | -|---|---|---| -| **Reports** (per-meeting summary with Read Score 0-100, Sentiment, Engagement metrics) | Recordings (per-meeting summary, transcript, action items) | **Knowcap missing**: numeric "Read Score" engagement metric. Cheap to compute from existing Gemini classifier + speaker timeline. | -| **Folders** (personal / shared / smart) | Projects | Read's smart-folder concept (auto-rules) is the same logic as Knowcap's routines — we have it, they have it. | -| **Ask Read** (chat across all meetings + integrations) | Knowcap chat | Parity. Both grounded RAG over user's meeting corpus. | -| **Smart Scheduler Link** (15 / 30 / 60 / 90 min defaults + custom) | **NONE** | Calendly-killer baked into a meeting tool. Easy add — uses the same Google Calendar OAuth scope Knowcap already has. | -| **CRM Recommendations** (auto-suggests Salesforce/HubSpot stage moves from meeting content) | SMEtools CRM agent (separate skill) | Read embeds this in their main product. Knowcap has the LLM + the transcripts but doesn't push CRM moves inside Knowcap UI. | -| **Coaching mode** (post-meeting feedback for the user — what they said, where they could improve) | **NONE** | Hassan flagged this as interesting at [13:14] of the walkthrough. Different from our live-tip layer in meet-full-prod (which is intra-call); this is async post-meeting. | -| **Ada digital twin** (cross-platform — Windows, MacOS, Android, iPhone, Chrome — "ask Ada anything via email") | **NONE** | Email-addressable AI personal assistant. Hassan flagged at [26:37]. Separate product, possibly more aspirational than shipped. | -| **MCP server** (Feb 25 2026 blog: "Read AI MCP: Your Meetings Just Became Your Most Powerful Dev Tool" — generates FastAPIs from transcripts, integrates with Claude Code + VS Code) | [[project_knowcap_mcp]] (knowcap-mcp wraps Knowcap API as MCP for Claude Code) | **Direct competitor.** Read's claim is more ambitious (auto-generates APIs from meeting content). Knowcap's MCP is simpler / more straightforward — read transcripts, write tasks, etc. | -| **Desktop app for in-person meetings** | **NONE** | Knowcap is browser-first. No way for Hassan to record an in-person sales call without a separate recorder app. | -| **Chrome extension** (300K+ users) | Knowcap extension (smaller install base) | Read's extension is the on-ramp to their desktop app. Knowcap extension has parity for browser-only capture but no desktop integration. | - -## Pricing (verbatim from Hassan's screenshots at [11:36] and [12:06]) - -- **Pro** — $19.75/mo per license. Unlimited meeting transcripts, 100 file-upload credits/mo. -- **Enterprise** (Most Popular) — $29.75/mo per license. 200 file-upload credits/mo. Premium integrations. -- **Enterprise+** — $39.75/mo per license, 5+ licenses minimum. 300 file-upload credits/mo. HIPAA compliance. Premium support. -- All tiers: annual saves 25%. -- 7-day free trial on Enterprise tier (no card required to start — Hassan got dropped in directly). - -For positioning: Knowcap's current pricing is below all three tiers, which is the right wedge for now (early-stage, undercut the incumbent). Once Knowcap hits feature parity on the missing pieces (Smart Scheduler, Coaching, CRM Recommendations), the $19-29/license band is where pricing should land. - -## Compliance posture (Read.ai homepage [29:48]) - -- **SOC 2 Type 2 Certified** ✅ -- **GDPR Compliant** ✅ -- **HIPAA Compliant** ✅ (Enterprise+ only) - -Knowcap has none of these certifications yet. Plan-side note: HIPAA gates the US healthcare TAM entirely; SOC 2 Type 2 is the table-stakes for enterprise sales conversations. Neither is needed for Knowcap's current ICP (founders, small teams), but they show up as objection-handlers in sales calls. - -## Capture-architecture comparison (the technical bit) - -``` - READ.AI KNOWCAP (post-PR #562) - ┌─────────────┐ ┌─────────────────────┐ - │ Desktop App │ ──── system audio │ Bot (Recall-style) │ ─── existing - │ + Extension │ ──── screen share │ (paid ~$0.70/hr) │ - └─────────────┘ │ │ - │ │ OR │ - │ getDisplayMedia │ │ - ▼ │ chrome.tabCapture │ ─── meet-full-prod PR - ┌────────────────┐ │ (Meet tab → PCM → │ - │ Meet tab │ │ AssemblyAI WS) │ - │ (no bot user) │ └─────────────────────┘ - └────────────────┘ - + - Google Calendar OAuth (scheduling only, - NOT for media ingest) -``` - -**Verdict:** Knowcap's `tabCapture` path in meet-full-prod PR #562 is **architecturally identical** to what Read.ai does inside their extension. Where they diverge: - -1. **Read has a desktop app that captures system audio outside the browser.** Knowcap doesn't — if Hassan's on an in-person call or non-browser meeting (FaceTime, native Zoom desktop client without browser), Knowcap can't capture. This is a real gap. -2. **Read's extension is the same path PR #562 uses,** but Read polishes the in-meeting UX (the "Join from Read AI" card on the home dashboard, the auto-detected upcoming-meeting suggestions) — Knowcap has the plumbing, needs the product polish. -3. **Read does NOT use the Meet REST API for ingest.** Knowcap meet-full-prod ALSO uses the Meet REST API (`conferenceRecords.recordings`, `transcripts.entries`) as a SECOND, post-call path. That's actually a Knowcap advantage — Read.ai users can't capture if their desktop app isn't running or their extension misses the start, whereas Knowcap can backfill via the Meet REST API after the fact (provided the user enabled Meet's native record). - -## Strategic opportunities for Knowcap - -Ranked by ROI (cheapest to ship that closes a Read-specific advantage): - -1. **Smart Scheduler Link** — Calendly competitor inside Knowcap. Reuses existing Calendar OAuth scope. ~2-3 days. Adds a SKU that doesn't exist on Read's free trial — could be a free tier add. -2. **Read Score / Sentiment metrics on the meeting card** — Knowcap already classifies sentiment in PR #562 (live + post). Add it to the Recordings list view as a chip. ~1 day. -3. **Coaching mode (async, post-meeting)** — Reuse Gemini Flash with a different prompt over the full transcript. ~2 days. Hassan flagged interest in this at [13:14]. -4. **MCP server hardening** — knowcap-mcp already exists ([[project_knowcap_mcp]]). Match Read.ai's MCP blog by publishing a public docs page + 3 example workflows. ~1 day. Marketing win. -5. **Desktop app** — biggest gap, biggest cost. Electron wrapper around an existing screen+audio capture. Probably 2-3 weeks. Not urgent until users complain about in-person meeting capture. -6. **CRM Recommendations inside Knowcap** — pull SMEtools CRM agent's logic into Knowcap proper. ~1 week. Wraps existing work. -7. **HIPAA / SOC 2 Type 2** — sales-cycle blocker. Don't ship until first enterprise inbound. 6-12 month process. - -## Surprises (worth flagging Hassan) - -- **Read.ai's "no bot" claim is technically true but it leans hard on screen-share consent dialogs.** Every meeting requires the user to grant `getDisplayMedia` ONCE. After that it's persistent. Knowcap's tabCapture path inherits the same UX cost. -- **Their MCP server (Feb 2026) is the strongest competitive signal.** They are positioning as a dev tool, not a meeting tool. This is the same lane Knowcap MCP plays in. We are not behind — but we are not loud about it. Marketing problem, not engineering problem. -- **Free trial is 7 days on Enterprise** — they default-aim users at the expensive tier with the trial. Knowcap's free path is more generous, which is the right wedge for adoption but worse for revenue conversion. - -## Marketing-site corroboration (Apify run `P0XH1VG9VnxZR5mDi`, 87 pages, finished 2026-05-19 16:21) - -Read.ai's own marketing pages back the walkthrough findings — with three additions worth flagging: - -1. **`/desktop` page is explicit** (verbatim): _"Record and summarize meetings without needing a bot. In person discussions, 1:1s, Slack Huddles? The Desktop app has you covered."_ — confirms zero bot, AND tells us their desktop app captures **Slack Huddles** (browser+desktop hybrid call surface). Knowcap doesn't. - -2. **`/extension` page lists 4 functions** (verbatim): - - Ask Search Copilot questions across your meetings - - View and join in-progress meetings - - Instantly add Read to live calls - - Copy your Smart Scheduler link - - So the extension is the on-ramp for both the live-add flow AND the scheduler link. The scheduling link is positioned as a first-class extension feature, not buried in the web app. - -3. **`/coaching` page reveals the metric framework** (verbatim): _"Speaker Metrics establish baselines around Clarity, Inclusion, and Impact using past meeting data."_ — three specific axes, not just a generic "engagement score." This is a more defensible product surface than I'd estimated. Knowcap would need to define its own 3-axis framework or copy these directly. - -4. **`/recommendations` page is broader than CRM-stage moves**: their headline claim is _"1 in 3 meeting participants are unnecessary."_ The recommendations engine identifies low-participation attendees and proposes: - - Mark a meeting participant optional or remove - - Change the time or length of a meeting - - Review a meeting series for deletion - This is _calendar-hygiene_ AI, not _CRM-update_ AI. The CRM Recommendations Hassan saw in the report card during onboarding are a separate surface inside Reports. - -5. **`/agents` page** — Read positions an entire "Agentic Workflow Suite." Direct competitor to Knowcap's project routines. Their pitch: _"Each agent works independently or as part of a coordinated team."_ Same architecture story Knowcap tells. - -6. **Localisation footprint** — site is fully translated to it / es / pt / fr / ja / hi / de / ru / zh, each with its own `/plans-pricing` page. That's 9 non-English markets with localised pricing. Knowcap is English-only. Localisation is a moat, not a feature. - -7. **Digital Twin "Ada"** — `/digital-twin` page confirms it's a shipped product, not aspirational. Three sub-skills: - - Ada Answers (knowledge-base Q&A) - - Ada Schedules (post-meeting "schedule next steps, send invites") - - Ada Covers For You ("get caught up with ease after vacation") - Marketed as **free**. So they're using it as a top-of-funnel acquisition lever for the paid tiers. - -## Followups / open questions - -- [x] When Apify run `P0XH1VG9VnxZR5mDi` finishes, append the marketing-site claim list to `architecture.md` — see section above. ✅ 2026-05-19 -- [ ] Cross-reference with Recall.ai, Otter.ai, Fathom, Granola, Tactiq — Read.ai is one of ~6 active competitors. Next research pass. -- [ ] Decide whether Smart Scheduler Link is a Knowcap V2 P0 — Hassan to weigh in. -- [ ] Decide on the 3-axis Knowcap speaker-metrics framework (vs Read's Clarity/Inclusion/Impact). -- [ ] Knowcap localisation — punt or plan? Cheap with current LLM costs. - -## Memory diff - -Old memory [[reference_readai_architecture]] said: "Read.ai uses BOTH Google Meet API and a bot." -That's wrong on both halves — they use neither. Updating that memory in the same commit as this doc lands. diff --git a/docs/research/competitors/read.ai/index.md b/docs/research/competitors/read.ai/index.md deleted file mode 100644 index c690511..0000000 --- a/docs/research/competitors/read.ai/index.md +++ /dev/null @@ -1,15 +0,0 @@ -# Competitor: Read.ai - -**URL:** https://www.read.ai/ -**Last refreshed:** 2026-05-19 -**Tier:** Direct competitor (same ICP, same product surface — AI meeting notetaker + assistant) - -## Files in this folder - -- [`architecture.md`](architecture.md) — Full technical + product breakdown. Capture mechanism, surfaces, pricing, opportunities. -- **Apify scrape dataset** (NOT in this repo) — Raw Apify website-content-crawler dataset, run ID `P0XH1VG9VnxZR5mDi` (2026-05-19), 87 read.ai pages. Stored in `llm-wiki` per the 2026-05-25 rule (research artifact, not marketing copy). - -## Source recordings - -- Hassan's own 30-min Knowcap walkthrough of Read.ai onboarding — `~/Downloads/Read.ai Onboarding and Setup Walkthrough.txt` -- Read.ai MCP launch blog (Feb 25 2026) — referenced inside the walkthrough at [23:57] diff --git a/docs/research/competitors/read.ai/positioning.md b/docs/research/competitors/read.ai/positioning.md deleted file mode 100644 index 6d55741..0000000 --- a/docs/research/competitors/read.ai/positioning.md +++ /dev/null @@ -1,191 +0,0 @@ -# Read.ai vs Knowcap — Sales positioning - -_Rewritten 2026-05-19 after the trust-layer vision reframe ([VISION.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/VISION.md), [POSITIONING.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/POSITIONING.md), [MOAT.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/MOAT.md)). Sister doc to [`architecture.md`](architecture.md) (technical breakdown) and [`index.md`](index.md). This file is the marketing/sales angle._ - -## TL;DR for sales - -**Read.ai is not our real competitor.** Glean, Zep, Tana, and Otter's April 2026 pivot are the real threats. Read.ai is a notetaker; Knowcap is a trust layer for AI agents. We do not fight them in their category — we sell into a different buyer with a different need. - -If a prospect compares us to Read.ai, the win condition is **reframe the conversation onto agent trust and audit-readiness**, not feature-by-feature notetaker comparison. We lose feature-by-feature; we win when "your AI agents need a human-confirmed source they can act on safely" lands. - ---- - -## The two-sentence positioning - -| Use | Sentence | -|---|---| -| **Cold outreach / landing page hero** | *"Most AI agents act on what the AI thinks is true. Knowcap agents act only on what a human said is true."* | -| **Formal sales conversation / technical deep-dive** | *"Knowcap is the trust layer for AI agents — every fact they act on is confirmed by a named human, with a full audit trail."* | - -Brand line for footers and badges: *"Verified knowledge for AI agents. Humans confirm. Agents act."* - ---- - -## Honest comparison — Read.ai's actual strengths - -Where Read.ai genuinely wins today (sales must acknowledge these, not hand-wave): - -- **Notetaker UX is more polished** for the meeting-recap-emailed-to-me use case -- **9-language localization** with per-locale pricing pages -- **300K+ Chrome extension installs** — distribution and social proof we don't have -- **Mature Zoom integration**; we lean Meet -- **MCP server** ("Read AI MCP: Your Meetings Just Became Your Most Powerful Dev Tool," Feb 2026) — they were not first to meeting MCP but they shipped one before us -- **Ada digital twin** — fully autonomous email-addressable agent, free tier — in production today -- **CRM write-back** to Salesforce / HubSpot — live recommendations push live stage moves (sales reps see ROI in week 1) -- **Compliance posture** — HIPAA on Enterprise+ -- **In-call coaching and scheduling links** — surfaces we don't have - -Three claims we previously made that we are RETIRING (they don't survive contact with Read.ai's reality): - -- ❌ *"They give your agents documents. We give them verified facts."* — Read's MCP and `Ask Read` already give structured access. The verified-vs-unverified distinction is invisible until our gate ships end-to-end. -- ❌ *"Read.ai literally cannot answer 'what risks are still open from Q1?'"* — Their `Ask Read` answers questions like this via RAG over summaries today. Not as graph-traversal accurate, but the buyer can't tell the difference in a demo. -- ❌ *"This is not a feature gap. It's a category difference. Read.ai cannot become Knowcap without rebuilding their data model from scratch."* — Read could ship a `review_status` column and a "verified" pill on summaries in one quarter. The category framing is the cope a smaller team uses when a bigger team is two PRs away. Don't lead with it. - ---- - -## Where Knowcap genuinely wins - -Two structural advantages that survive the competitive scan. Both are **partially shipped** as of 2026-05-19 — sales must be honest about that. - -### 1. Human attestation as a queryable primitive - -Read.ai stores meeting summaries with a disclaimer: *"Outputs are generated by AI and may be inaccurate or require human review."* That disclaimer is for legal cover, not a primitive their agents can act on differently. Every Read summary is treated as ground truth by `Ask Read`, the CRM Recommendations engine, and Ada. - -Knowcap stores every memory with a `review_status` column. A human's explicit confirmation moves a memory from `pending` (claim) to `evidence`. Agents query the graph through MCP with a required `verification_strictness` parameter — they cannot accidentally read unverified claims if they were registered as `human_only`. - -**Read would need to rewrite every downstream feature to filter on a verification state they don't store.** This is the moat — but only if our gate is wired end-to-end through `memoryService`, RAG, and MCP. As of 2026-05-19 there are 3 known ignore-sites in production where unverified claims leak through. Closing those (target: 30 days) makes this moat real in shipped behavior, not just on paper. - -### 2. The regulatory floor - -This is the real reason we win against Read.ai for the buyers who matter most. - -| Regulation | What it mandates | Effective | -|---|---|---| -| EU AI Act Article 14 | Natural-person oversight for high-risk AI systems | Aug 2 2026 | -| GDPR Article 22 | Human intervention right for automated decisions with legal effect | In force | -| ESMA MiFID II Statement | Investment firm decisions remain management's responsibility, non-delegable to AI | May 2024 | -| CMS Medicare Advantage Final Rule | AI may inform, cannot decide; physician review required on denials | Jan 1 2024 | -| ABA Formal Opinion 512 | Lawyers may not rely on AI outputs "without independent verification" | Jul 2024 | -| Moffatt v. Air Canada | Companies legally liable for everything their AI agent says | 2024 precedent | - -These do not say "verify because AI hallucinates." They say "a human must attest." Read.ai's disclaimer is not an attestation primitive — it's a disclaimer. Our `confirmed_by` user_id + timestamp + source clip IS the regulated artifact. - -**~55-65% of enterprise AI spending sits in industries where the human signature is the regulated artifact** (Gartner GenAI 2025 + McKinsey sector breakdown). This is the buyer Knowcap targets. Read.ai targets the other ~35-45%. - ---- - -## The one example query that genuinely separates us - -The four "queries Read.ai cannot answer" we previously listed were misleading — three of them Read can answer via `Ask Read` today, just less accurately. There is ONE we should keep because it actually requires edge traversal that RAG over summaries cannot fake: - -> _"Which supplier has caused the most unresolved risks across the last 18 months?"_ - -This requires a Party → Risk → no `mitigated_by` edge traversal across many meetings. RAG over summaries cannot do this — the summaries don't carry the edge. Read.ai has no edge layer. **Honest caveat:** Knowcap's typed-edge layer is targeted for Sprint 3 (post-2026-05-26) and is not buildable into demos today. Use this query on the roadmap conversation, not the today-demo conversation. - ---- - -## Buyer profile — who we sell to - -### Buyer 1 — Odoo partners (Phase 1, now → 12 months) -- Boutique-to-mid-market consulting firms (10–200 employees) implementing Odoo for clients -- Pain: client meeting decisions on SOW scope are litigated months later; partner has informal audit trail (email threads, WhatsApp) -- Knowcap pitch: meeting → human-confirmed scope decision (client confirms too via cross-org bridge) → bulletproof audit trail -- Lighthouse demo target (2026-07-31): meeting → confirmed claim → auto-generated Odoo SH PR -- Hassan's distribution advantage: SMEtools is an Odoo partner; he knows the segment, the conferences, the WhatsApp groups - -### Buyer 2 — Regulated knowledge work (Phase 2, month 6 → year 2) -- Financial advisors (FINRA Rule 3110, MiFID II) -- Boutique-to-mid-market law firms (ABA Op. 512, attorney-client privilege) -- Healthcare admin (CMS MA Final Rule) -- Compliance officers at mid-size companies -- Pain: their regulator requires human attestation on AI-assisted decisions; EU AI Act enforcement Aug 2 2026 is a forcing function -- Knowcap pitch: audit-ready human confirmation infrastructure under EU AI Act Article 14 -- Pricing: $100-500/seat/month range vs Read.ai's $19-39 productivity tiers - -### Anti-buyer — DO NOT sell here -- Founders, PMs, sales reps, marketing teams looking for "better meeting summaries" -- They want accurate summaries + CRM sync; the verification UX is friction they don't value -- Lifetime value is low; churn is high -- Refer them politely to Granola or Fathom. Tell them we'll be ready when their compliance officer is. - ---- - -## What's shipped today vs aspirational (sales source of truth) - -Sales must not promise vapor. This matrix is the truth. - -| Capability | Status today | What sales can say | -|---|---|---| -| Meeting capture (Meet + recordings) | Shipped | "We capture every meeting" | -| Visual transcription + OCR + speaker ID | Shipped | "We extract from visuals + audio + speakers" | -| Claim extraction (5 categories) | Shipped | "We classify every memory into 5 actionable categories, org-tunable" | -| Pending → Evidence confirmation gate UX | Shipped | "Humans confirm each claim before it's used" | -| `review_status` enforced in chat + RAG + MCP | **GAP** — 3 ignore-sites | DO NOT DEMO end-to-end yet. Fix target: 30 days. | -| Typed edges (`mitigated_by`, `superseded_by`, etc.) | **Not shipped** | DO NOT PROMISE. Roadmap conversation only. Target Sprint 3 post-2026-05-26. | -| Instructions Hierarchy (org/project/user) | In progress | "Coming May 23" | -| Knowcap MCP for external agents | Shipped (without strictness param) | "Your agents query our verified facts via MCP" — caveat: strictness parameter ships with the gate fix | -| Cross-org confirmation (Parties) | Partial UI | "Pilot soon" — not for general sales yet | -| Atlas visual graph | Shipped (mockup data quality varies) | "Visual graph view exists" — show in demos | -| Parties as Knowcap-native CRM substrate | Shipped | "Profile per party with sentiment arc + cross-source bridges" | -| Odoo SH PR lighthouse demo | **Not built** | Roadmap conversation. Target 2026-07-31. | - -**Demo discipline:** lead with MCP + Parties + Atlas + 5-category classification. These are shipped, demoable, and prove the trust-layer thesis at the architectural layer. Save typed edges, trust ladder graduation, agent marketplace, and the Odoo SH demo for the roadmap conversation. - ---- - -## When this angle WINS - -- Buyers wiring up AI agents who need a trusted knowledge substrate (dev tools, autonomous ops, AI agencies) -- Regulated buyers with explicit human-attestation mandates (financial advisors, legal, healthcare admin) -- Compliance officers shopping for EU AI Act Article 14 tooling (June-December 2026 window) -- Odoo partners with client SOW-attestation pain (Hassan's distribution segment) -- Founders running multiple orgs who want cross-org confirmation bridges -- Procurement / supply-chain teams who genuinely need "which supplier has the most unresolved risks?" — *once edges ship* - -## When this angle LOSES - -- Buyers who just want meeting recaps emailed to them — Read's UX is more polished -- Buyers who need HIPAA day one — Read has it on Enterprise+; we don't -- Buyers who need 300K+ extension installs as social proof -- Buyers using Zoom > Meet primarily — Read's Zoom integration is more mature -- Buyers who only attend in-person meetings — Read has a desktop app; we don't -- Buyers who view AI agents as a 2027-2028 concern — they pick the better notetaker today, revisit later - ---- - -## Pricing positioning - -| Tier | Read.ai | Knowcap (now) | Knowcap (post-gate-wire-up) | Knowcap (regulated vertical) | -|---|---|---|---|---| -| Entry | $19.75/license/mo (Pro) | Free / lower | $19/license/mo | n/a | -| Mid | $29.75/license/mo (Enterprise) | — | $29/license/mo | n/a | -| Enterprise | $39.75/license/mo, 5+ seats, HIPAA | — | Match price post-HIPAA cert | $100-500/seat/mo | - -Knowcap's free-and-low wedge is right for early productivity-curious adoption. The pricing leverage is in the regulated-vertical tier — that buyer pays 5-10× the productivity-buyer rate because their regulator demands the verification artifact. - ---- - -## The EU AI Act window (June - December 2026) - -Aug 2 2026 is when high-risk AI systems under the EU AI Act become enforceable (current Digital Omnibus deferral could push to Dec 2027 — monitor monthly). Between June and December 2026, every regulated buyer in Europe will Google "EU AI Act Article 14 compliance" looking for tooling. - -**Positioning moves to land before the window peaks:** -- Publish a "Knowcap and EU AI Act Article 14" technical brief by 2026-06-15 -- Add "Article 14 compliance" copy to the landing page hero by 2026-06-30 -- Outbound campaign to EU-based RIA / law firm / fractional CFO networks 2026-07-01 → 2026-09-30 -- Land 3-5 regulated-vertical pilot customers by 2026-09-30 - -While Read.ai and Glean are still selling "summaries" and "search," we are the only player selling "audit-ready human confirmation infrastructure under EU AI Act Article 14." - ---- - -## Source material - -- [`architecture.md`](architecture.md) — technical breakdown of Read's capture stack, surfaces, compliance, scraped pages -- [`index.md`](index.md) — folder index -- [Knowcap VISION.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/VISION.md) — trust-layer thesis -- [Knowcap POSITIONING.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/POSITIONING.md) — internal positioning doc -- [Knowcap MOAT.md](https://github.com/Knowcap-V2/knowcap-marketing/blob/main/docs/brand/MOAT.md) — why verification survives 100% AI accuracy -- Hassan's own 30-min Read.ai onboarding walkthrough at `~/Downloads/Read.ai Onboarding and Setup Walkthrough.txt` -- Apify scrape of 87 read.ai marketing pages: dataset `YufiMdMvsnZ0j3zAc`, stored in llm-wiki not here (research artifact, not marketing material) -- Competitive analysis conducted 2026-05-19 across 4 parallel research agents + 1 multi-attendee design research agent — findings consolidated into the docs above diff --git a/docs/research/data/MENA-LINKEDIN-COUNTS.csv b/docs/research/data/MENA-LINKEDIN-COUNTS.csv deleted file mode 100644 index 7a09c22..0000000 --- a/docs/research/data/MENA-LINKEDIN-COUNTS.csv +++ /dev/null @@ -1,33 +0,0 @@ -country,filter,count,timestamp -UAE,total,200,000,1780330575 -UAE,size_11-50,30,000,1780330586 -UAE,size_51-200,10,000,1780330599 -UAE,size_201-500,3,800,1780330611 -KSA,total,80,000,1780330622 -KSA,size_11-50,10,000,1780330634 -KSA,size_51-200,7,500,1780330646 -KSA,size_201-500,2,500,1780330657 -Egypt,total,80,000,1780330670 -Egypt,size_11-50,10,000,1780330682 -Egypt,size_51-200,6,200,1780330693 -Egypt,size_201-500,2,300,1780330705 -Jordan,total,NO_MATCH,1780330715 -Jordan,size_11-50,NO_MATCH,1780330725 -Jordan,size_51-200,NO_MATCH,1780330735 -Jordan,size_201-500,NO_MATCH,1780330744 -Kuwait,total,NO_MATCH,1780330754 -Kuwait,size_11-50,NO_MATCH,1780330764 -Kuwait,size_51-200,NO_MATCH,1780330773 -Kuwait,size_201-500,NO_MATCH,1780330782 -Qatar,total,20,000,1780330793 -Qatar,size_11-50,3,400,1780330805 -Qatar,size_51-200,1,500,1780330816 -Qatar,size_201-500,644,1780330828 -Lebanon,total,20,000,1780330840 -Lebanon,size_11-50,2,200,1780330851 -Lebanon,size_51-200,780,1780330862 -Lebanon,size_201-500,280,1780330874 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-EG,ar_meeting_notes,"محضر اجتماع",ERROR,0 -EG,ar_meeting_notes,"مذكرات الاجتماع",ERROR,0 -EG,ar_meeting_notes,"تلخيص اجتماع",ERROR,0 -EG,ar_meeting_notes,"محاضر اجتماعات",ERROR,0 -EG,ar_ai,"ذكاء اصطناعي",1.4,262 -EG,ar_ai,"ذكاء اصطناعي",ERROR,0 -EG,ar_ai,"تشات جي بي تي",ERROR,0 -EG,ar_ai,"شات جي بي تي",ERROR,0 -EG,ar_ai,"ChatGPT",ERROR,0 -EG,ar_odoo,"أودو",0.1,262 -EG,ar_odoo,"أودو",ERROR,0 -EG,ar_odoo,"اودو",ERROR,0 -EG,ar_odoo,"Odoo",ERROR,0 -EG,ar_scope,"تغيير النطاق",0.2,262 -EG,ar_scope,"تغيير النطاق",ERROR,0 -EG,ar_scope,"خلاف عميل",ERROR,0 -EG,ar_scope,"نطاق العمل",ERROR,0 -EG,ar_scope,"اتفاقية العمل",ERROR,0 -EG,ar_docs,"إجراءات تشغيل",0.6,262 -EG,ar_docs,"إجراءات تشغيل",ERROR,0 -EG,ar_docs,"وثيقة المشروع",ERROR,0 -EG,ar_docs,"محضر القرار",ERROR,0 -EG,ar_docs,"تقرير العميل",ERROR,0 -EG,ar_verticals,"وكالة تسويق",0.2,262 -EG,ar_verticals,"وكالة تسويق",ERROR,0 -EG,ar_verticals,"شركة استشارات",ERROR,0 -EG,ar_verticals,"مكتب محاسبة",ERROR,0 -EG,ar_verticals,"مكتب محاماة",ERROR,0 -EG,ar_franco,"enaktab",0.2,262 -EG,ar_franco,"كناب",48.6,262 -EG,ar_franco,"enaktab",ERROR,0 -EG,ar_franco,"كناب",ERROR,0 -EG,ar_franco,"noukap",ERROR,0 -JO,ar_meeting_notes,"محضر اجتماع",0.6,262 -JO,ar_meeting_notes,"محضر اجتماع",ERROR,0 -JO,ar_meeting_notes,"مذكرات الاجتماع",ERROR,0 -JO,ar_meeting_notes,"تلخيص اجتماع",ERROR,0 -JO,ar_meeting_notes,"محاضر اجتماعات",ERROR,0 -JO,ar_ai,"ذكاء اصطناعي",1.4,262 -JO,ar_ai,"ذكاء اصطناعي",ERROR,0 -JO,ar_ai,"تشات جي بي تي",ERROR,0 -JO,ar_ai,"شات جي بي تي",ERROR,0 -JO,ar_ai,"ChatGPT",ERROR,0 -JO,ar_odoo,"أودو",0.1,262 -JO,ar_odoo,"أودو",ERROR,0 -JO,ar_odoo,"اودو",ERROR,0 -JO,ar_odoo,"Odoo",ERROR,0 -JO,ar_scope,"تغيير النطاق",0.0,262 -JO,ar_scope,"تغيير النطاق",ERROR,0 -JO,ar_scope,"خلاف عميل",ERROR,0 -JO,ar_scope,"نطاق العمل",ERROR,0 -JO,ar_scope,"اتفاقية العمل",ERROR,0 -JO,ar_docs,"إجراءات تشغيل",0.4,262 -JO,ar_docs,"إجراءات تشغيل",ERROR,0 -JO,ar_docs,"وثيقة المشروع",ERROR,0 -JO,ar_docs,"محضر القرار",ERROR,0 -JO,ar_docs,"تقرير العميل",ERROR,0 -JO,ar_verticals,"وكالة تسويق",0.3,262 -JO,ar_verticals,"وكالة تسويق",ERROR,0 -JO,ar_verticals,"شركة استشارات",ERROR,0 -JO,ar_verticals,"مكتب محاسبة",ERROR,0 -JO,ar_verticals,"مكتب محاماة",ERROR,0 -JO,ar_franco,"enaktab",0.6,262 -JO,ar_franco,"كناب",7.4,262 -JO,ar_franco,"enaktab",ERROR,0 -JO,ar_franco,"كناب",ERROR,0 -JO,ar_franco,"noukap",ERROR,0 -KW,ar_meeting_notes,"محضر اجتماع",2.0,262 -KW,ar_meeting_notes,"محضر اجتماع",ERROR,0 -KW,ar_meeting_notes,"مذكرات الاجتماع",ERROR,0 -KW,ar_meeting_notes,"تلخيص اجتماع",ERROR,0 -KW,ar_meeting_notes,"محاضر اجتماعات",ERROR,0 -KW,ar_ai,"ذكاء اصطناعي",0.4,262 -KW,ar_ai,"ذكاء اصطناعي",ERROR,0 -KW,ar_ai,"تشات جي بي تي",ERROR,0 -KW,ar_ai,"شات جي بي تي",ERROR,0 -KW,ar_ai,"ChatGPT",ERROR,0 -KW,ar_odoo,"أودو",0.4,262 -KW,ar_odoo,"أودو",ERROR,0 -KW,ar_odoo,"اودو",ERROR,0 -KW,ar_odoo,"Odoo",ERROR,0 -KW,ar_scope,"تغيير النطاق",0.7,262 -KW,ar_scope,"تغيير النطاق",ERROR,0 -KW,ar_scope,"خلاف عميل",ERROR,0 -KW,ar_scope,"نطاق العمل",ERROR,0 -KW,ar_scope,"اتفاقية العمل",ERROR,0 -KW,ar_docs,"إجراءات تشغيل",0.8,262 -KW,ar_docs,"إجراءات تشغيل",ERROR,0 -KW,ar_docs,"وثيقة المشروع",ERROR,0 -KW,ar_docs,"محضر القرار",ERROR,0 -KW,ar_docs,"تقرير العميل",ERROR,0 -KW,ar_verticals,"وكالة تسويق",0.4,262 -KW,ar_verticals,"وكالة تسويق",ERROR,0 -KW,ar_verticals,"شركة استشارات",ERROR,0 -KW,ar_verticals,"مكتب محاسبة",ERROR,0 -KW,ar_verticals,"مكتب محاماة",ERROR,0 -KW,ar_franco,"enaktab",0.3,262 -KW,ar_franco,"كناب",2.0,262 -KW,ar_franco,"enaktab",ERROR,0 -KW,ar_franco,"كناب",ERROR,0 -KW,ar_franco,"noukap",ERROR,0 -QA,ar_meeting_notes,"محضر اجتماع",0.0,262 -QA,ar_meeting_notes,"محضر اجتماع",ERROR,0 -QA,ar_meeting_notes,"مذكرات الاجتماع",ERROR,0 -QA,ar_meeting_notes,"تلخيص اجتماع",ERROR,0 -QA,ar_meeting_notes,"محاضر اجتماعات",ERROR,0 -QA,ar_ai,"ذكاء اصطناعي",0.0,262 -QA,ar_ai,"ذكاء اصطناعي",ERROR,0 -QA,ar_ai,"تشات جي بي تي",ERROR,0 -QA,ar_ai,"شات جي بي تي",ERROR,0 -QA,ar_ai,"ChatGPT",ERROR,0 -QA,ar_odoo,"أودو",0.0,262 -QA,ar_odoo,"أودو",ERROR,0 -QA,ar_odoo,"اودو",ERROR,0 -QA,ar_odoo,"Odoo",ERROR,0 -QA,ar_scope,"تغيير النطاق",0.3,262 -QA,ar_scope,"تغيير النطاق",ERROR,0 -QA,ar_scope,"خلاف عميل",ERROR,0 -QA,ar_scope,"نطاق العمل",ERROR,0 -QA,ar_scope,"اتفاقية العمل",ERROR,0 -QA,ar_docs,"إجراءات تشغيل",0.2,262 -QA,ar_docs,"إجراءات تشغيل",ERROR,0 -QA,ar_docs,"وثيقة المشروع",ERROR,0 -QA,ar_docs,"محضر القرار",ERROR,0 -QA,ar_docs,"تقرير العميل",ERROR,0 -QA,ar_verticals,"وكالة تسويق",0.0,262 -QA,ar_verticals,"وكالة تسويق",ERROR,0 -QA,ar_verticals,"شركة استشارات",ERROR,0 -QA,ar_verticals,"مكتب محاسبة",ERROR,0 -QA,ar_verticals,"مكتب محاماة",ERROR,0 -QA,ar_franco,"enaktab",0.0,262 -QA,ar_franco,"كناب",0.7,262 -QA,ar_franco,"enaktab",ERROR,0 -QA,ar_franco,"كناب",ERROR,0 -QA,ar_franco,"noukap",ERROR,0 -LB,ar_meeting_notes,"محضر اجتماع",0.0,262 -LB,ar_meeting_notes,"محضر اجتماع",ERROR,0 -LB,ar_meeting_notes,"مذكرات الاجتماع",ERROR,0 -LB,ar_meeting_notes,"تلخيص اجتماع",ERROR,0 -LB,ar_meeting_notes,"محاضر اجتماعات",ERROR,0 -LB,ar_ai,"ذكاء اصطناعي",0.2,262 -LB,ar_ai,"ذكاء اصطناعي",ERROR,0 -LB,ar_ai,"تشات جي بي تي",ERROR,0 -LB,ar_ai,"شات جي بي تي",ERROR,0 -LB,ar_ai,"ChatGPT",ERROR,0 -LB,ar_odoo,"أودو",0.2,262 -LB,ar_odoo,"أودو",ERROR,0 -LB,ar_odoo,"اودو",ERROR,0 -LB,ar_odoo,"Odoo",ERROR,0 -LB,ar_scope,"تغيير النطاق",0.0,262 -LB,ar_scope,"تغيير النطاق",ERROR,0 -LB,ar_scope,"خلاف عميل",ERROR,0 -LB,ar_scope,"نطاق العمل",ERROR,0 -LB,ar_scope,"اتفاقية العمل",ERROR,0 -LB,ar_docs,"إجراءات تشغيل",0.4,262 -LB,ar_docs,"إجراءات تشغيل",ERROR,0 -LB,ar_docs,"وثيقة المشروع",ERROR,0 -LB,ar_docs,"محضر القرار",ERROR,0 -LB,ar_docs,"تقرير العميل",ERROR,0 -LB,ar_verticals,"وكالة تسويق",0.0,262 -LB,ar_verticals,"وكالة تسويق",ERROR,0 -LB,ar_verticals,"شركة استشارات",ERROR,0 -LB,ar_verticals,"مكتب محاسبة",ERROR,0 -LB,ar_verticals,"مكتب محاماة",ERROR,0 -LB,ar_franco,"enaktab",0.0,262 -LB,ar_franco,"كناب",0.4,262 -LB,ar_franco,"enaktab",ERROR,0 -LB,ar_franco,"كناب",ERROR,0 -LB,ar_franco,"noukap",ERROR,0 -MA,ar_meeting_notes,"محضر اجتماع",2.3,262 -MA,ar_meeting_notes,"محضر اجتماع",ERROR,0 -MA,ar_meeting_notes,"مذكرات الاجتماع",ERROR,0 -MA,ar_meeting_notes,"تلخيص اجتماع",ERROR,0 -MA,ar_meeting_notes,"محاضر اجتماعات",ERROR,0 -MA,ar_ai,"ذكاء اصطناعي",0.1,262 -MA,ar_ai,"ذكاء اصطناعي",ERROR,0 -MA,ar_ai,"تشات جي بي تي",ERROR,0 -MA,ar_ai,"شات جي بي تي",ERROR,0 -MA,ar_ai,"ChatGPT",ERROR,0 -MA,ar_odoo,"أودو",0.0,262 -MA,ar_odoo,"أودو",ERROR,0 -MA,ar_odoo,"اودو",ERROR,0 -MA,ar_odoo,"Odoo",ERROR,0 -MA,ar_scope,"تغيير النطاق",0.0,262 -MA,ar_scope,"تغيير النطاق",ERROR,0 -MA,ar_scope,"خلاف عميل",ERROR,0 -MA,ar_scope,"نطاق العمل",ERROR,0 -MA,ar_scope,"اتفاقية العمل",ERROR,0 -MA,ar_docs,"إجراءات تشغيل",0.3,262 -MA,ar_docs,"إجراءات تشغيل",ERROR,0 -MA,ar_docs,"وثيقة المشروع",ERROR,0 -MA,ar_docs,"محضر القرار",ERROR,0 -MA,ar_docs,"تقرير العميل",ERROR,0 -MA,ar_verticals,"وكالة تسويق",0.0,262 -MA,ar_verticals,"وكالة تسويق",ERROR,0 -MA,ar_verticals,"شركة استشارات",ERROR,0 -MA,ar_verticals,"مكتب محاسبة",ERROR,0 -MA,ar_verticals,"مكتب محاماة",ERROR,0 -MA,ar_franco,"enaktab",0.2,262 -MA,ar_franco,"كناب",2.5,262 -MA,ar_franco,"enaktab",ERROR,0 -MA,ar_franco,"كناب",ERROR,0 -MA,ar_franco,"noukap",ERROR,0 \ No newline at end of file diff --git a/docs/research/data/trends-mena-interest.csv b/docs/research/data/trends-mena-interest.csv deleted file mode 100644 index 80f47a9..0000000 --- a/docs/research/data/trends-mena-interest.csv +++ /dev/null @@ -1,102 +0,0 @@ -country,group,query,avg_interest_0_100,n_weeks -AE,meeting_tools,"meeting notes",2.7,262 -AE,meeting_tools,"Otter.ai",0.8,262 -AE,meeting_tools,"Read.ai",1.0,262 -AE,meeting_tools,"Fireflies.ai",0.2,262 -AE,ai_adoption,"ChatGPT",30.3,262 -AE,ai_adoption,"AI agent",0.1,262 -AE,ai_adoption,"Claude AI",0.3,262 -AE,knowcap_adj,"Odoo",52.9,262 -AE,knowcap_adj,"scope creep",0.0,262 -AE,knowcap_adj,"client portal",0.6,262 -AE,doc_pain,"SOP template",0.1,262 -AE,doc_pain,"project documentation",5.9,262 -AE,doc_pain,"client report",1.3,262 -SA,meeting_tools,"ERROR",,0 -SA,ai_adoption,"ChatGPT",28.8,262 -SA,ai_adoption,"AI agent",0.1,262 -SA,ai_adoption,"Claude AI",0.5,262 -SA,knowcap_adj,"Odoo",49.2,262 -SA,knowcap_adj,"scope creep",0.1,262 -SA,knowcap_adj,"client portal",0.0,262 -SA,doc_pain,"SOP template",0.1,262 -SA,doc_pain,"project documentation",5.9,262 -SA,doc_pain,"client report",1.5,262 -EG,meeting_tools,"meeting notes",1.7,262 -EG,meeting_tools,"Otter.ai",0.6,262 -EG,meeting_tools,"Read.ai",0.5,262 -EG,meeting_tools,"Fireflies.ai",0.4,262 -EG,ai_adoption,"ChatGPT",27.5,262 -EG,ai_adoption,"AI agent",0.1,262 -EG,ai_adoption,"Claude AI",0.7,262 -EG,knowcap_adj,"Odoo",57.2,262 -EG,knowcap_adj,"scope creep",0.0,262 -EG,knowcap_adj,"client portal",0.0,262 -EG,doc_pain,"SOP template",0.2,262 -EG,doc_pain,"project documentation",4.0,262 -EG,doc_pain,"client report",0.7,262 -JO,meeting_tools,"meeting notes",0.4,262 -JO,meeting_tools,"Otter.ai",0.0,262 -JO,meeting_tools,"Read.ai",0.0,262 -JO,meeting_tools,"Fireflies.ai",0.0,262 -JO,ai_adoption,"ChatGPT",32.1,262 -JO,ai_adoption,"AI agent",0.1,262 -JO,ai_adoption,"Claude AI",0.5,262 -JO,knowcap_adj,"Odoo",25.8,262 -JO,knowcap_adj,"scope creep",0.0,262 -JO,knowcap_adj,"client portal",0.2,262 -JO,doc_pain,"SOP template",0.3,262 -JO,doc_pain,"project documentation",2.2,262 -JO,doc_pain,"client report",0.0,262 -KW,meeting_tools,"meeting notes",0.8,262 -KW,meeting_tools,"Otter.ai",0.5,262 -KW,meeting_tools,"Read.ai",0.7,262 -KW,meeting_tools,"Fireflies.ai",0.0,262 -KW,ai_adoption,"ChatGPT",28.7,262 -KW,ai_adoption,"AI agent",0.1,262 -KW,ai_adoption,"Claude AI",0.3,262 -KW,knowcap_adj,"Odoo",39.2,262 -KW,knowcap_adj,"scope creep",0.0,262 -KW,knowcap_adj,"client portal",0.4,262 -KW,doc_pain,"SOP template",0.3,262 -KW,doc_pain,"project documentation",0.7,262 -KW,doc_pain,"client report",0.6,262 -QA,meeting_tools,"meeting notes",0.0,262 -QA,meeting_tools,"Otter.ai",0.4,262 -QA,meeting_tools,"Read.ai",0.2,262 -QA,meeting_tools,"Fireflies.ai",0.4,262 -QA,ai_adoption,"ChatGPT",22.9,262 -QA,ai_adoption,"AI agent",0.0,262 -QA,ai_adoption,"Claude AI",0.2,262 -QA,knowcap_adj,"Odoo",34.4,262 -QA,knowcap_adj,"scope creep",0.2,262 -QA,knowcap_adj,"client portal",0.0,262 -QA,doc_pain,"SOP template",0.0,262 -QA,doc_pain,"project documentation",1.3,262 -QA,doc_pain,"client report",0.0,262 -LB,meeting_tools,"meeting notes",0.8,262 -LB,meeting_tools,"Otter.ai",0.0,262 -LB,meeting_tools,"Read.ai",0.3,262 -LB,meeting_tools,"Fireflies.ai",0.4,262 -LB,ai_adoption,"ChatGPT",32.1,262 -LB,ai_adoption,"AI agent",0.1,262 -LB,ai_adoption,"Claude AI",0.6,262 -LB,knowcap_adj,"Odoo",42.6,262 -LB,knowcap_adj,"scope creep",0.1,262 -LB,knowcap_adj,"client portal",0.2,262 -LB,doc_pain,"SOP template",0.3,262 -LB,doc_pain,"project documentation",0.5,262 -LB,doc_pain,"client report",0.3,262 -MA,meeting_tools,"meeting notes",0.4,262 -MA,meeting_tools,"Otter.ai",0.7,262 -MA,meeting_tools,"Read.ai",0.3,262 -MA,meeting_tools,"Fireflies.ai",0.0,262 -MA,ai_adoption,"ChatGPT",33.6,262 -MA,ai_adoption,"AI agent",0.0,262 -MA,ai_adoption,"Claude AI",0.6,262 -MA,knowcap_adj,"Odoo",53.8,262 -MA,knowcap_adj,"scope creep",0.0,262 -MA,knowcap_adj,"client portal",0.1,262 -MA,doc_pain,"SOP template",0.1,262 -MA,doc_pain,"project documentation",2.3,262 -MA,doc_pain,"client report",0.5,262 \ No newline at end of file diff --git a/docs/research/data/trends-mena-related.csv b/docs/research/data/trends-mena-related.csv deleted file mode 100644 index 1ebf7ef..0000000 --- a/docs/research/data/trends-mena-related.csv +++ /dev/null @@ -1,19 +0,0 @@ -country,seed_query,top_term,top_value -AE,"meeting notes","ai meeting notes",100 -AE,"meeting notes","meeting notes template",19 -AE,"meeting notes","zoom meeting",16 -AE,"meeting notes","meeting life challenges class 12 notes",16 -AE,"meeting notes","read.ai meeting notes",15 -AE,"meeting notes","read.ai meeting notes in teams",8 -AE,"meeting notes","otter ai",5 -AE,"meeting notes","fireflies ai",5 -SA,"meeting notes","ai meeting notes",100 -SA,"meeting notes","read.ai meeting notes",21 -SA,"meeting notes","meeting notes template",13 -SA,"meeting notes","read ai meeting notes",13 -SA,"meeting notes","read.ai meeting notes in teams",6 -SA,"meeting notes","read ai meeting notes in teams",3 -EG,"meeting notes","meeting notes template",100 -EG,"meeting notes","read.ai meeting notes",98 -EG,"meeting notes","read ai meeting notes in teams",45 -QA,"meeting notes","meeting notes template",100 \ No newline at end of file diff --git a/docs/research/data/trends-mena-rising.csv b/docs/research/data/trends-mena-rising.csv deleted file mode 100644 index fc43822..0000000 --- a/docs/research/data/trends-mena-rising.csv +++ /dev/null @@ -1,14 +0,0 @@ -country,seed_query,rising_term,rising_value -AE,"meeting notes","read.ai meeting notes",418050 -AE,"meeting notes","read.ai meeting notes in teams",211950 -AE,"meeting notes","otter ai",130350 -AE,"meeting notes","fireflies ai",126150 -AE,"meeting notes","ai meeting notes",1050 -AE,"meeting notes","meeting life challenges class 12 notes",90 -AE,"meeting notes","zoom meeting",80 -SA,"meeting notes","ai meeting notes",3011100 -SA,"meeting notes","read ai meeting notes",377200 -SA,"meeting notes","read.ai meeting notes in teams",183200 -SA,"meeting notes","read ai meeting notes in teams",77250 -EG,"meeting notes","read.ai meeting notes",686750 -EG,"meeting notes","read ai meeting notes in teams",316250 \ No newline at end of file diff --git a/docs/research/data/youtube-mena-pain-comments.csv b/docs/research/data/youtube-mena-pain-comments.csv deleted file mode 100644 index 1e5f932..0000000 --- a/docs/research/data/youtube-mena-pain-comments.csv +++ /dev/null @@ -1,88 +0,0 @@ -video_id,channel_title,category,matched_term,text_snippet,like_count -"wCiXnCg4Z8Y","Odoo Tutorials","odoo","Odoo","ക്യാഷ് റൗണ്ടിംഗ് ഡിഫോൾട്ട് ആയി സെറ്റ് ചെയ്യാൻ പറ്റുന്നില്ല...ഓരോ ബില്ലും ചെയ്യേണ്ടി വരുന്നു..odoo 18",1 -"cTE4T31qhvo","Odoo Mates","odoo","Odoo","For Odoo 13 and below, download and use our free module from odoo store. Odoo 13: https://apps.odoo.com/apps/modules/13.0/om_sa_invoice/ Odoo 12: https://apps.odoo.com/apps/modules/12.0/om_sa_invoice/ Odoo 11: https://apps.odoo.com/apps/modules/11.0/om_sa_invoice/ Odoo 10: https://apps.odoo.com/app",0 -"cTE4T31qhvo","Odoo Mates","odoo","Odoo","HI hOW can i embed xml with custom invoice in odoo?",0 -"cTE4T31qhvo","Odoo Mates","odoo","Odoo","Thank you for providing valuable tutorials. I found one issue with the Odoo QR Code. I have some Invoices with Retention so I set two taxes for a product. For example, for one product there will be VAT tax of 15% and a Retention of 5% and I set the Retention as -5%. In the subtotal, it shows correct",1 -"hqqzVpqCe24","Webkul","odoo","Odoo","https://webkul.com/odoo-implementation-services/",0 -"hqqzVpqCe24","Webkul","odoo","Odoo","Which Odoo module is best for MBA finance students to learn and use in their jobs etc ? Any best answer please ?",0 -"GjER--Dy8qI","Odoo","odoo","Odoo","Hi Odoo Team, where can I get steps to do Odoo implementation process as technically?",1 -"RI2l5VWSCK4","ODOO IT YOURSELF","odoo","Odoo","Your videos are super valuable, thank you! It would be great to hear some advice for aspiring self starters wanting to get into the Odoo dev game. What to look out for and risks and opportunities. Where would you start your business as a one man team with a PC, Internet and a moderate knowledge of ",1 -"RI2l5VWSCK4","ODOO IT YOURSELF","odoo","Odoo","End user here. Been trying to learn Odoo for 7 months now. I had NO idea it would be this impossibly difficultz",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","If you're watching this and thinking 'I'd rather just have someone set this up for me', I get it. I put together three ways I can help depending on where you're at → https://www.odooityourself.com/r/ZQN",2 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","ERP","Would this essentially replace the need for bigger ERP solutions for small businesses? For App like inventory, would someone still have to book every inventory movement manually into a terminal with browser? Could a Handscanner or forklift be made to interface to it while not connected to a sit d",2 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","In the free account if one is using Odoo Accounting module only, does it restrict any features.",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","very much helpful, you have explained everything so easily, one quick question, can we make Odoo for (Multi-company, multi-currency)",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","How do you see the path and barriers of starting de odoo journey to become a partner, what do you think about the industry given the actual technology tools that ease the technical challenges",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","Thanks for this. Great video. You said that Odoo doesn't do payroll but if I Google ""does Odoo have payroll?"" it seems that it does? My wife an I are setting up a two person small retail business. We don't need complexity. It sounds like a vanilla out of the box Odoo setup might work for us? Though ",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","excellent info bro in a very short time. Does Odoo support production ?",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","Thank you, very helpful . my questions are is Odoo good for small business start-ups and is the application free ?",2 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","I want to market nursing ceus to nurses. So, I need a way to accept payments and issue certificates. Training would be done via slides (PowerPoint or other). Can Odoo do this?",1 -"QuC6rc2q2mg","ODOO IT YOURSELF","odoo","Odoo","@ODOO IT YOURSELF - Odoo allows custom UX/UI ?",1 -"6kdlJrLXwRA","Waleed Maestro","odoo","Odoo","odoo 18 نفس الخطوات ؟",0 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","ERP","هل يمكن عمل نظام ERP باستخدام برنامج ال Access و برنامج ال My SQL ؟",0 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","هل ممكن تعطينا مصادر تعلم odoo و sap ?",1 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","Odoo REST Module ظننت هو الحل للنقطة اللي ذكرتها في نهاية الليس كذلك؟",0 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","هل ai هياثر علي مجال Odoo Developer وهستبداله او يقلل الطلبه علي المجال من وجهه نظرك حضرتك بما انك شغل في المجال ده",0 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","اشتغلت مطور odoo لمدة 3 اشهر بعدين الشركة مشتني 😂 قعدت احاول اتعلم odoo development طوال ال3 اشهر لكن كان صعب جدا بدون مصادر تعلم",12 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","كلام صحيح نسبيا ولكن: إتخاذ قرار الأنظمة المستخدمة في الشركة هو قرار إداري، مع الأخذ بعين الإعتبار الجانب التقني وليس العكس! يعتمد على أهداف الشركة البعيدة والقريبة، الميزانية، مجال الشركة وآلية عملها، السرعة في التنفيذ لمواكبة المتغيرات السريعة في المجالات التنافسية. SAP & Salesforce وغيرها من الأن",1 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","براييك باش مهندس ك هل امتلاك خبرة بمجال الodoo تقصد odoo devloperاقدر أعمل customize للسيستم يبقى مطلوية بسوق العمل؟",1 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","خطا يا استاذ بل يوجد في api json في نظام odoo",4 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","أودو","مظبوط لأن المفروض الشخص يروح لشركة محترمة تنفذ ليه المشروع بكل سهولة و خصوصا الشركات اللي بتبقا متعاقدة مع اودو انا شغال قي شركة وكيل رسمي لأودوو و بننفذ مشاريع اودو للشركات المتوسطة و الصغيرة و بنقدم كل الخدمات دي و بنعمل انتجريشن و ربط مع انظمة كتير مختلفة و الحمد لله نفذنا حوالي 40 مشروع لشركة و",4 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","ERP","ملاحظة صغيرة، salesforce هو CRM مش ERP و ده اختصار customer relationship management, مثال تاني لاشهر الerp systems يبقى حاجة زي SAP كده",7 -"EddDhIpA5F0","Yehia Tech يحيى تك","odoo","Odoo","عشان كده يا هندسه في erp system جاي تاني وبقوه وهو next من شركه frappe وفي صعود جامد جدا واظن هيعدي odoo واهم ميزه فيه هو سهل جدا في ال integration مع كل المواقع لانه open source بردو واحسن من odoo في features اعلي منه بكتير وده عن واقع تجربه",18 -"6GOkRhedFzs","TechnoFunctionalLearning","odoo","Odoo","I installed odoo 19 on termux but i am getting css error on the website. Did you use python venv? What version of python ? 3.12 or 3.10? What version of libsass and lxml?",0 -"u7UZWSaYNJ8","Software Connect","odoo","ERP","Explore Software for Small Businesses: https://softwareconnect.com/go/small-business-erp-9ede5",2 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","As a businessman I would prefer Zoho, as a developer I would love to choose Odoo. Odoo gives me freedom to create my own modules, customize things as I like, but Zoho gives me easy and fast access to tools, essential customisation only.",105 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","Starting out my own company and I plan to use Zoho One (for the bulk business operations) and Odoo MRP app (single app paid). After I will work on connecting the two via N8N with custom APIs and workflows between Odoo MRP and Zoho Books and CRM for my software and hardware products.",34 -"u7UZWSaYNJ8","Software Connect","odoo","ERP","As an Srilankan ERP consultant i prefer both",0 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","I'm trying to decide between this 2, for a small business that does maintenance services and spare parts, so mainly I am focusing on FSM and Inventory and how they connect between each other, I was leaning for Odoo because It looks cleaner/more stable, but I realized that Odoo doesnt offer GPS track",1 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","Great video. I just had a very bad experience with Odoo.. they deleted all my data out of an update they even didn't know how it was scheduled without my consent. Support : we can't do much!",0 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","As a developer zoho is best, Odoo has too much flaws also it seems expensive.",13 -"u7UZWSaYNJ8","Software Connect","odoo","ERP","what about erpnext ?",0 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","Actually Odoo is not a friendly user😢",1 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","Great video, thanks for the comparison! I run a construction startup and I have three main needs: 1. ERP for subcontractor/vendor management, material tracking, and overall operations 2. Facebook leads integration directly into CRM 3. Payroll for employees, all within a reasonable budget Bet",2 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","Just checking out Zoho as I have used Odoo since 2023 (Community) and enterprise from end of (2024), the pricing part is bit outdated from 2024, Odoo has been at $11 per user per month on Standard and $18 per user per month on Custom plan..we implemented the custom plan in Dec 2024, the $18 actual",0 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","This guy is clearly selling odoo, while trying to be fair to Zoho. Nice try.",0 -"u7UZWSaYNJ8","Software Connect","odoo","Odoo","Odoo is open source which is safer than zoho. & its an indian company is precisely why its not safe. All ypur data is esentially govt data. No thankyou",0 -"vZE0j_WCRvI","Good Work","odoo","ERP","""Go to meetings and prepare for meetings."" Accurate. We hire consultants and they just sit in meetings and create PowerPoints to show at the next meeting to show what was in the previous meeting.",7443 -"vZE0j_WCRvI","Good Work","odoo","ERP","My ex girlfriend left me for a young consultant so this is extremely gratifying, thank you. I was a secure overachiever, which is why I'm an underpaid artist.",3846 -"vZE0j_WCRvI","Good Work","odoo","ERP","26 yo Management Consultant here. ""Going to meetings and preparing for meetings"" is a very good description. At best you take on some menial tasks that still have some tangible value at least. At worst, your job is simply to agree with the client, fiddle with some PowerPoint slides, and show up to m",493 -"gg9jncbu14g","Murrad on Run","odoo","ERP","I don't know why this woman is portraying DUBAI as something out of the league as if she's the niece of Dubai's king. If her point of view is to be considered then those who are astrologers in india even they are consultants in their capacity and earn more than their counterparts working in delloite",3 -"qzdnIG4VBRc","E-Accounting & ERP","odoo","أودو","شكرا على الشرح المبسط والرائع. سؤال لو سمحت هل يمكن ربط نظام كامتند الخاص بالحضور والانصراف عن طريق الجوال بنظام أودو؟ لو ممكن شرح للموضوع في فيديو منفصل من فضلك.",4 -"qzdnIG4VBRc","E-Accounting & ERP","odoo","Odoo","محتاجة اتعلم odoo sales",0 -"5yY_KMBM03o","putcodes","odoo","Odoo","انا محاسب ومذاكر python وعاوز اكون Odoo developer ممكن ترشحلى كورس ابدا معاه",1 -"5yY_KMBM03o","putcodes","odoo","Odoo","هل ai هياثر علي مجال Odoo Developer وهستبداله او يقلل الطلبه علي المجال من وجهه نظرك حضرتك بما انك شغل في المجال ده",2 -"5yY_KMBM03o","putcodes","odoo","Odoo","لو سمحت في حد بيقدم تدريب ليodoo",1 -"5yY_KMBM03o","putcodes","odoo","Odoo","لو سمحت انا odoo developer منين اجيب مشاريع جاهزة واتعلم منها واطبق",1 -"5yY_KMBM03o","putcodes","odoo","ERP","هو erp Consultant غير erp developer صح ؟؟؟",1 -"5yY_KMBM03o","putcodes","odoo","Odoo","لو سمحت هو مرتبات odoo implementer في مصر والخليج في رينج كام؟",1 -"5yY_KMBM03o","putcodes","odoo","Odoo","انا عندي مشاكل في تثبيت odoo على لينكس هل في فرق اذا على ويندوز او لينكس",0 -"4hTgxJR5qmo","غريب الشيخ || Ghareeb Elshaikh","odoo","Odoo","عندى سؤال لحضرتك دلوقت لو محتاج erp system عندى فى شركه لسه بقوم بأنشائها اقدر اشترك فى odoo واعمل ال implementation بنفسى . ولا هكون محتاج customization كتير على odoo enterprise ؟!",0 -"4hTgxJR5qmo","غريب الشيخ || Ghareeb Elshaikh","odoo","Odoo","عايز اسأل حضرتك موضوع ال partnership مع odoo كويس ولا لا ؟",0 -"4hTgxJR5qmo","غريب الشيخ || Ghareeb Elshaikh","odoo","Odoo","طب اى إمكانيات الجهاز لتشغيل odoo",0 -"4hTgxJR5qmo","غريب الشيخ || Ghareeb Elshaikh","odoo","Odoo","هل إذا حملت Odoo Community 18 على سيرفر في البيت بحصل كل هذه المميزات؟",0 -"l9RkbMPW3Qw","Ahmed Hassan Algammal ","odoo","ERP","صراحة بسبب أن اودو مبني ببايثون فده بيدي إمكانيات جبارة للشركة اللي بتفهم سواء تحليل البيانات أو التكامل مع الذكاء الاصطناعي وقد يتفوق في الحتت دي على erp زي SAP ,Oracle وغيرهم بسبب أن المعمارية بتاعتهم قديمة و أصعب من الناحية دي في التطوير",1 -"l9RkbMPW3Qw","Ahmed Hassan Algammal ","odoo","Odoo","السلام عليكم أنا طالب فرقة رابعة تجارة وعاوز اشتغل في مجال ERP حضرتك تنصحني اتعلم علي odoo ولا SAP وجزاك الله خيرا",2 -"l9RkbMPW3Qw","Ahmed Hassan Algammal ","odoo","ERP","ممكن ي هندسه تدينا رودماب لو حد حابب يبدا في مجال ال erp ازاي يبدا ويختار انهي نظام وكنو حابب اعرف من حضرتك ايه اكتر نظام منتشر ف الخليج",1 -"l9RkbMPW3Qw","Ahmed Hassan Algammal ","odoo","ERP","وليه ما نعملش erp يكون منتج عربي زي ما الهنود عندهم tally, erp next , ZOHO ...",1 -"l9RkbMPW3Qw","Ahmed Hassan Algammal ","odoo","ERP","السلام عليكم انا اسف يا بشمهندس سؤال برا الفيديو انا هتخرج من هندسة اتصالات الترم دا وعاوز أتخصص في مجال من مجالات آل erp بس يكون صعب ان الذكاء الاصطناعي يستبدله ترشحلي اي حتى لو هحتاج دراسة بزنس معاه وجزاك الله خير مقدما واسف على الإطالة",1 -"FMM-Gb76ydQ","Growth Way","odoo","Odoo","Wow, this is hands down the best Odoo explanation video I've come across! The clarity and thoroughness with which you covered each module are truly commendable. Great job!",0 -"I0qpNCg4rMo","Ambience Hub","meeting_en","MoM","Great to know that videos like this exist. Especially perfect if you have disappointed parents who call you frequently! No mom, I’m not playing video games, I’m filling out a TPS report!",165 -"I0qpNCg4rMo","Ambience Hub","meeting_en","MoM","Corporate Accounts Payable, Nina speaking! Just a moment!",13 -"0GL9adXduJY","Income Interviews ","odoo","ERP","She’s underpaid",5 -"sFVYR_KalBI","Rawaa | رواء","ai_curious","ذكاء اصطناعي","‏ اعملي فيديو عن Gemini بليز وعن أفضل برنامج ذكاء اصطناعي♥️🙏🏻",81 -"sFVYR_KalBI","Rawaa | رواء","ai_curious","ChatGPT","رواء اخو صحبيتي عمرو ثمن سنين قالي مرة انو يريد يتعلم شلون يتسخدم ChatGPT بس ما عرفت شلون اعلمه فا الحمد لله انك عملتي فيديو بسيط و من خبيرة جزاك الله خيرا رواء",14 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the ChatGPT Pro Plan more precise and high-quality answers. I want responses identical to those from the paid pro version",93 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the chatGPT pro plane for more precise and high-quality answers. I want responses indentical to those from the paid pro version",34 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the chatGPT pro plane for more precise and -quality answers . I want responses identical to those from the paid pro version",24 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the ChatGPT Pro plane for more precise and high-quality answers .I wat responses identical to those from the paid pro version",2 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the ChatGPT plane for more precise and high-quailty answers. I want pesponses identical to those from the paid pro version",0 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the ChatGPT pro plane for more precise and high-quality answers . I want responses identical to those from the paid pro version.",4 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the chatgpt pro plane for more precise and high_quality answers . I want resposes identcal to those from the piad pro version",1 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","Use the ChatGPT pro plane for more precise and high-quality answers . I want responses identical to😂 those from the paid pro version",0 -"f3wYmrQxORc","عرب تكنو - 3rab techno","ai_curious","ChatGPT","# Use the ChatGPT pro plane for more precise and high-quality answers. I want responses identical to those from the paid pro version",1 -"eEJEPIjieeg","Mohamed Medhat - محمد مدحت","ai_curious","ChatGPT","شكرا محمد انت متميز بهذا الموضوع اشرح اكثر عن ChatGPT ونريد فيديوهات عن ادوات الذكاء في التعليم الجامعي والبحث العلمي",1 -"eEJEPIjieeg","Mohamed Medhat - محمد مدحت","ai_curious","ChatGPT","الله يعطيك العافيه فيديو جميل انا كمان بخطط للسفر مع chatgpt",2 -"PKsth1zHVtg","TOOLBOXLAP","ai_curious","ChatGPT","شكرا علي الشرح لكن المشكلة لسنا كلنا نملك credit card ان امكن تمدنا بفيزا وهمية تشتغل علي chatgpt",2 -"hPrb5DSzUI4","Nehal SpaceTech","ai_curious","ChatGPT","جميل بس طيب هو دا chatgpt 5 ولا هو 4 ولما ادفع يتحول 5 عاوزه افهم دي",0 -"hPrb5DSzUI4","Nehal SpaceTech","ai_curious","ChatGPT","إذا شريت كونت chatgpt plus واش نقدر نحلو ف 4 لبيسيات ؟",1 diff --git a/docs/research/data/youtube-mena-videos.csv b/docs/research/data/youtube-mena-videos.csv deleted file mode 100644 index 9ef9d5e..0000000 --- a/docs/research/data/youtube-mena-videos.csv +++ /dev/null @@ -1,97 +0,0 @@ -query,video_id,channel_title,title,view_count,published_at -"Odoo Saudi Arabia","wCiXnCg4Z8Y","Odoo Tutorials","ZATCA E-Invoicing Integration in Odoo19 | Saudi Arabia VAT Compliance | സൗദി അറേബ്യ ഇ-ഇൻവോയ്‌സിങ്",1553,"2025-12-06" -"Odoo Saudi Arabia","UUTjRagDkis","Apagen Solutions Pvt. Ltd.","Odoo Demo - Saudi VAT Invoice | Apagen Solutions Pvt. Ltd. (Odoo Service Provider)",671,"2021-01-08" -"Odoo Saudi Arabia","hFdKw6rd-tk","HMPRO","Zatca Saudi Arabia - E-invoicing Fixes for Odoo",724,"2025-09-15" -"Odoo Saudi Arabia","3TIc_7Te6jE","Odoo Tutorials","ZATCA Phase 2 Integration Saudi Arabia in Odoo19 Explained | Odoo Tutorials Malayalam",288,"2026-02-27" -"Odoo Saudi Arabia","VMsZ7zUMn5E","Technaureus Info Solutions Pvt. Ltd.","Odoo MyFatoorah Mada Payment Gateway Integration | Saudi Arabia Mada Payment in Odoo",457,"2025-07-30" -"Odoo Saudi Arabia","cTE4T31qhvo","Odoo Mates","Enable Saudi Arabia ZATCA E-Invoicing In Odoo | Free ZATCA POS software | Zakat Billing Software",13277,"2021-11-30" -"Odoo Saudi Arabia","MHryEp5wqOg","HMPRO","Saudization & Nitaqat Compliance Tracker – Odoo KSA",80,"2025-09-23" -"Odoo Saudi Arabia","c3BHRcBMR1U","Sharek","كيف تربط Odoo مع هيئة الضرائب ZATCA في السعودية ؟",1580,"2025-12-11" -"Odoo UAE implementation","hqqzVpqCe24","Webkul","7 Steps for Successful Odoo Implementation",1391,"2025-02-03" -"Odoo UAE implementation","7h1BSpEUhlE","Glorium Technologies","Odoo Pricing: What is the Real Odoo Implementation Cost?",35540,"2025-06-03" -"Odoo UAE implementation","GjER--Dy8qI","Odoo","From Kickoff to Go-Live: Managing an Odoo ERP Project Implementation on Odoo 19",2242,"2025-11-18" -"Odoo UAE implementation","HsZ85jgdcm8","Techbot","Odoo 19: Digital Transformation, Automation & E-Invoicing for UAE Businesses",142,"2025-11-06" -"Odoo UAE implementation","RI2l5VWSCK4","ODOO IT YOURSELF","Five Different Ways to Approach Your Odoo Implementation",1185,"2023-10-28" -"Odoo UAE implementation","6_nxcQoO5rE","Odoo ERP by O2B Technologies Experts","How to Quickstart Your Odoo ERP Implementation | Step-by-Step Guide – O2B Technologies",12297,"2022-11-16" -"Odoo UAE implementation","QuC6rc2q2mg","ODOO IT YOURSELF","Odoo Beginner's Guide",153355,"2025-07-03" -"Odoo UAE implementation","axwx1kmHCtQ","Learn with Tauseef Ahmed","Odoo ERP Pricing Explained | Hosting, Implementation & Licensing Cost (Complete Guide 2025/2026)",251,"2025-12-11" -"Odoo Egypt","lAYZ1-Ac2nQ","Odoo Arabic","Agile Business Transformation: Mimar Models Egypt & Odoo",119,"2026-04-01" -"Odoo Egypt","6kdlJrLXwRA","Waleed Maestro","Egyptian E-Invoice + Odoo: The Only Complete Integration Tutorial You Need!",3052,"2024-08-11" -"Odoo Egypt","EddDhIpA5F0","Yehia Tech يحيى تك","ايه هو نظام Odoo ؟ 🟣🙄",157637,"2024-01-17" -"Odoo Egypt","Un0GJ7FhqvU","B Smart Odoo Egypt","0151ربط الايصال الالكتروني بمصر باودو ETA POS Electronic Receipt Egypt Odoo",306,"2025-10-24" -"Odoo Egypt","LTEzZfRxQ8E","Techstation Egypt","Create Odoo on Our Platform in Under 2 Minutes",33,"2025-09-08" -"Odoo Egypt","6GOkRhedFzs","TechnoFunctionalLearning","Demo Odoo ERP 18 (Open Source):CRM App on Android Mobile with Local PostgreSQL Database",195773,"2025-05-19" -"Odoo Egypt","u7UZWSaYNJ8","Software Connect","Odoo vs. Zoho One (2026) Which One Actually Works for Your Business?",48424,"2025-04-11" -"Odoo Egypt","JlAWsEWeU6w","Odoo","Webinar - Launch your online store with Odoo",1561,"2026-03-26" -"SME owner Dubai","9IjeJnaImps","Dubai Chambers ","Dubai Business Growth -- SME Finance",610,"2012-11-06" -"SME owner Dubai","RneaUL-xdlE","Jitendra Consulting Group","Benefits of Hiring Audit Firms in Dubai for Startups & SMEs",17,"2022-07-05" -"SME owner Dubai","8h1cGXdrlmo","Crunch DUBAI","Dubai SME, Ms. Rania Sheir has 15 years of experience there! Monologue at 24SIX9 Founders Community",539,"2024-06-29" -"SME owner Dubai","brTYR1ubmKk","GLOBALS tv","Why doing business in Dubai? Dubai SME CEO",153,"2019-02-27" -"SME owner Dubai","IKxl3fGl5a4","Vision.ae","Dubai Means Business - SME",285,"2014-10-23" -"SME owner Dubai","TTFrxe9w-OM","Danube Properties","Our Founder and Chairman, Mr. Rizwan Sajan welcomes Mr. H.E Abdul Baset Al Janahi, CEO Dubai SME",1330,"2024-06-04" -"SME owner Dubai","8xZ3QoDi-kE","Middle East Bulletin","Sabir Shaikh Wins Outstanding Leader Award for SME Empowerment at Masterminds | UAE Business Growth",78,"2025-06-25" -"SME owner Dubai","vnEECrDuFts","SME District","CEO of SME District & Hashtag Department Store Intreview WIth Dubai One Tv",46,"2023-10-09" -"business owner Saudi","TTKLKJ5V5cQ","Ali Gul Chandio ","Start Your Business in Saudi Arabia with 100% Ownership| Kia ap company kholna chahty hen saudia me ",2333,"2026-04-04" -"business owner Saudi","9E2b2ynS2Eg","Zayan Perdasi ","Can you really make that much money in the trolley business in Saudi Arabia? This trolley driver won",265888,"2025-09-25" -"business owner Saudi","Yz1mKUYWtFo","5 Ideas","🇸🇦 5 Small Business Ideas for Saudi Arabia | Profitable Business In Saudi Arabia",77579,"2023-06-14" -"business owner Saudi","vj0GZWq6tyo","Ahmad Mushtaq","What kind of business you can start as a foreigner in Saudi Arabia? #MISA #SAGIA #KSA",18751,"2021-08-25" -"business owner Saudi","UwOkNamcrWA","Beesolv","Amazon Saudi Arabia Sourcing #amazon #ecommerce #business #viral #reels #pakistan #saudiarabia",46926,"2024-04-03" -"business owner Saudi","1GswLfB_HAs","My life In Saudi Arabia ","Start Business in Saudi Arabia CR & LLC Guide 2025",11622,"2025-06-15" -"business owner Saudi","TqGBzax5cSg","Shakeel Ahmad Meer","Real Estate Business Secrets - Riyadh Saudi Arabia | Shakeel Ahmad Meer",8357,"2025-08-07" -"business owner Saudi","w3s87zlXA_4","Import Export with Usman","🤑 Low INVESMENT Starting from restaurant business in Saudia Arabia",17779,"2025-04-10" -"consulting agency Dubai","plZP6IxyaqY","Shiraz Waheed - SetupHero","How to Start a Consulting Business in Dubai (Step-by-Step 2025)",361,"2025-12-15" -"consulting agency Dubai","WWEgL466x9E","Aimdubai24 ","DIRECT JOBS IN DUBAI 2025-2026 through placement consultant #dubaijobs",347380,"2023-06-24" -"consulting agency Dubai","vyffDh38zgU","Saeed Shah","top recruitment agencies in Dubai | jobs in Dubai | Saeed shah",2899,"2025-02-27" -"consulting agency Dubai","YQQHAMSLcrc","Gulf Country Job","""Dubai Mall is Hiring NOW – 200+ Vacancies! 🚀"" #dubaijobs #jobsindubai #uaejobs #shorts",426956,"2025-06-10" -"consulting agency Dubai","vZE0j_WCRvI","Good Work","What does a consultant actually do?",2533007,"2023-03-08" -"consulting agency Dubai","D28BTlOa7Cs","DXB Helpdesk","Best Consultancy in Dubai for Europe. Europe country Work Visa. how to go European countries for Job",10331,"2025-01-17" -"consulting agency Dubai","PzQuyTS6rCE","The Thinksters - Career in Management consulting","Dubai consulting market – opportunities & salaries in 2025",1460,"2025-03-13" -"consulting agency Dubai","gg9jncbu14g","Murrad on Run","Getting a Management Consulting job in Dubai (Highest Paid Job in Dubai)",26502,"2025-04-16" -"أودو السعودية","qzdnIG4VBRc","E-Accounting & ERP","كل اللى محتاج تعرفه عن نظام Odoo و التعريف بالنظام الحلقه الأولى",623276,"2023-01-03" -"أودو السعودية","9w20xqiYsG0","Naqlah Technology Consulting","ما هو نظام Odoo - تعريف",52773,"2024-08-08" -"أودو السعودية","5yY_KMBM03o","putcodes","أشتغلت Odoo Developer في السعودية | تطوير Odoo و ERP للمبرمجين 💼🇸🇦",4566,"2025-06-15" -"أودو السعودية","efjAz1IqLhI","Kaizen principles","ERP افضل برنامج اودو في السعودية من شركة كايزن",719,"2022-12-31" -"أودو السعودية","4hTgxJR5qmo","غريب الشيخ || Ghareeb Elshaikh","إنشاء شركة من الصفر باستخدام أودو فقط - Odoo",33114,"2025-07-22" -"أودو السعودية","-RzXpPYAeog","E-Accounting & ERP","ادخال القيود اليومية Journal entries - برنامج Odoo الحلقة الرابعة",158010,"2023-02-05" -"أودو السعودية","l9RkbMPW3Qw","Ahmed Hassan Algammal ","اودو افشل نظام ادارة شركات ؟ الحقيقة الكاملة ",1968,"2025-12-09" -"أودو السعودية","FMM-Gb76ydQ","Growth Way","Odoo ERP أودو 18 المبيعات والمشتريات والحسابات",3725,"2024-10-26" -"اوديو شركة","I0qpNCg4rMo","Ambience Hub","Call Center Sounds - Work From Home - Office - Ambience",8783041,"2016-04-24" -"اوديو شركة","N3IA_u2sb28","bushra dawoud","الرد الآلي ( IVR ) لشركة الاتصالات | تعليق صوتي",20920,"2023-02-23" -"اوديو شركة","XuWzo5dX7IQ","L MIKROB الميكروب","اوديو أستاد الرياضيات معصب #اوديو #مضحك",4021,"2023-03-09" -"اوديو شركة","qrveekHoeJ4","محمد علي - Mohamed Ali","كيف تحصل على أعمال صوتية و تربح من صوتك ؟",93711,"2022-07-18" -"اوديو شركة","1ZBR23k0890","Rawaa | رواء","Boya microphone against DJI, who wins? #audio #mics #microphone",16387130,"2024-01-07" -"اوديو شركة","_73JBZDrMNo","قليلا من كل شيء","كيف يتم صنع سماعات الأذن الطبية؟ - خطوة بخطوة 😮 #shorts",39844154,"2023-11-01" -"اوديو شركة","dUdrm0YM1zU","king Abidos","مقدمة فيديو احترافية بدون إسم مجانا يبحث عنها الجميع #intro_اسمك #kingabidos #اليوتيوب #shorts",201763,"2023-04-19" -"اوديو شركة","AT7WguTjRNM","Mr WARTA GAMING","صوتي في ببجي موبايل 😂",3683376,"2025-04-12" -"ادارة المشاريع مصر","JXEXdbS5tsI","PMCORNERKSA","Project Management in 15 minutes | إدارة المشاريع في 15 دقيقة من خلال مثال عملي",144202,"2022-05-07" -"ادارة المشاريع مصر","yBwXYXl1I-w","Mostafa Attia","هذه هى تجربتى مع شهادة ادارة المشاريع PMP!! قبل ما تدبس شوف الفيديو دة!",110629,"2023-06-14" -"ادارة المشاريع مصر","2nU3_-2cypM","SAYED MOHSEN PMP","ما هى شهادة PMP وأهميتها فى سوق العمل",100139,"2023-07-10" -"ادارة المشاريع مصر","a9FeTk2zZLI","Ehab Mesallum","أهم 6 حاجات لازم تجهزهم قبل بداية البيزنيس | 144 | عيادة الشركات | د. إيهاب مسلم",438065,"2025-07-09" -"ادارة المشاريع مصر","f1yDazifWE0","NaviGrowth Project Management","( Project Management أهم فيديو قبل ما تبدأ تتعلم الـ ) !ازاي تكون مش مدير مشروع؟",28811,"2022-12-07" -"ادارة المشاريع مصر","xU6F6uNwF-c","MedSpark eLearning","Project Management for Healthcare Professionals (PMP) - إدارة المشاريع الاحترافية في الرعاية الصحية",466,"2024-11-26" -"ادارة المشاريع مصر","gXjcUBOh05Y","منصة عافر التعليمية - 3afer","إدارة المشروعات الصغيرة | المحاضرة الأولى - تجارة القاهرة",513,"2024-10-15" -"ادارة المشاريع مصر","ozqQbCmtNdI","Heba Alshehhi","أساسيات إدارة المشاريع بمنهجية أجايل سكرم Agile Scrum",159814,"2018-02-19" -"وكالة تسويق دبي","96XUCNjpc8Q","Ahmed Khalifa احمد خليفة","Marketing Agency بدأت شركة تسويق الكتروني بعائدات تصل الى 50,000$؟",104404,"2022-11-26" -"وكالة تسويق دبي","i2acwrP5AiE","Muhammad Ghazaly | محمد غزالى","إزاي تسوّق بميزانية قليلة؟💰📈#تسويق #تسويق_رقمي #تسويق_الكتروني #تسويق_بميزانية_قليلة #دبي #تسويقـدبي",129,"2025-02-02" -"وكالة تسويق دبي","67vpI8iocjA","Elie Khudari Archive | ايلي خضري - أرشيف","كيف تؤسس وكالة تسويق ناجحة | نصائح لانشاء شركة تسويق الكتروني وتقديم خدمات تسويقية احترافية",50914,"2022-03-10" -"وكالة تسويق دبي","8Nbhr4AvBHs","Muhammad Ghazaly | محمد غزالى","USPمش هتعرف تبيع أي حاجة من غير USP #تسويق #تسويق_إلكتروني #دبي #الرياض #marketingservices",457,"2025-03-03" -"وكالة تسويق دبي","KaKfNy27KRc","Anwr محمد أنور ","اسهل طريقة لفتح شركة في دبي _ محمد انور",48666,"2023-03-03" -"وكالة تسويق دبي","0GL9adXduJY","Income Interviews ","How much a Digital Marketing Exec makes in Dubai #Marketing #SocialMedia #Career #Salary",107674,"2025-02-18" -"وكالة تسويق دبي","UYwEd359mQE","بيتر دانيال - Peter Daniel","اكتر مجالين شغل مطلوبين في دبي 🇦🇪",2572086,"2023-02-17" -"وكالة تسويق دبي","JiPKOM3N5pI","shaheenDXB","تجربتي في مجال العقارات في دبي لمده سنتين",13526,"2024-08-02" -"ريادة اعمال السعودية","kjNsFLriPUA","HFA FIRM","الترخيص الريادي في السعودية لرواد الأعمال الأجانب الغير سعوديين",2650,"2025-08-22" -"ريادة اعمال السعودية","ZrFDqUtBKdQ","MBC1","نموذج لقصة نجاح أصغر رائد أعمال في العالم",173612,"2022-04-18" -"ريادة اعمال السعودية","J0NKQiVx2lA","MBC1","أسرار نجاح رائد الأعمال",109453,"2022-04-19" -"ريادة اعمال السعودية","aHU19xgbFM8","إذاعة ثمانية","كيف تبني شركة ريادية بأقل المخاطر | بودكاست سوالف بزنس",408907,"2025-01-06" -"ريادة اعمال السعودية","a_TAQv6hkR8","MBC1","أحمد الشقيري يوضح أهم أسباب فشل الشركات الناشئة",304439,"2022-04-19" -"ريادة اعمال السعودية","EeEPMd95uGQ","HFA FIRM","ما مصير الرخصة الريادية في السعودية مع القانون الجديد؟",2854,"2025-01-17" -"ريادة اعمال السعودية","ClQHs-wLEVc","Shark Tank Egypt","رائد أعمال رفض يبيع شركته مقابل ١٠٠ مليون دولار!",2064285,"2024-10-01" -"ريادة اعمال السعودية","6hg0jrVCFkw","Business بالعربي","٦ صفات لكي تكون رائد اعمال ناجح !- فلوج#16",85368,"2025-07-28" -"ChatGPT للأعمال","sFVYR_KalBI","Rawaa | رواء","دليلك الشامل لــ ChatGPT من الصفر | كيفية استخدام تشات جي بي تي للمبتدئين",281547,"2026-01-18" -"ChatGPT للأعمال","gF1vUQQvVU0","أكاديمية ريان | Ryan Academy","وفر مالك! خصم 95% على ChatGPT بزنس + 10 حسابات ChatGPT Business مجاناً!",1634,"2026-01-20" -"ChatGPT للأعمال","f3wYmrQxORc","عرب تكنو - 3rab techno","ازاي تاخد ChatGPT المدفوع !؟ 🔥😱 خطوة سهلة وبسيطة ✅",866475,"2025-06-24" -"ChatGPT للأعمال","fS-ltvjGG7Y","CodeX","أخيراً! الطريقة الجديدة لتفعيل ChatGPT Business مجانًا",517,"2025-12-30" -"ChatGPT للأعمال","u8IhvSSyNa0","Bassam Elyamany - بسام اليمني","ChatGPT Plus و Business مجاناً 2025 | الطريقة القانونية بالتفصيل",21366,"2025-10-31" -"ChatGPT للأعمال","eEJEPIjieeg","Mohamed Medhat - محمد مدحت","٧ استخدامات يومية لـشات جي بي تي هتغيّر حياتك حرفيًا - Chat GPT",153131,"2025-05-18" -"ChatGPT للأعمال","PKsth1zHVtg","TOOLBOXLAP","ChatGPT Business مجاناً 2025 🚀 السر القانوني بخطوات سهلة وشرح رسمي!",4724,"2025-11-02" -"ChatGPT للأعمال","hPrb5DSzUI4","Nehal SpaceTech","شرح ChatGPT وخطط الاشتراك الجديدة 2025 | Free – Go – Plus – Pro – Business",3351,"2025-10-21" diff --git a/docs/strategy/gtm-strategy.md b/docs/strategy/gtm-strategy.md deleted file mode 100644 index 5e450ad..0000000 --- a/docs/strategy/gtm-strategy.md +++ /dev/null @@ -1,33 +0,0 @@ -# Go-to-Market Strategy - -Two paid acquisition channels in the launch phase, with a third strategic path being debated. - -## Primary Channels - -### 1. Meta paid (Facebook + Instagram) -Run via StratDev agency. 90-day discovery sprint, $150–200/day spend, target sub-$50 CAC. Full plan in [`campaigns/meta-paid-sprint.md`](../campaigns/meta-paid-sprint.md). - -### 2. LinkedIn outbound -Run via Heyreach automation + Sales Navigator. ~4,500 messages/month across 3 accounts, target 20–25 booked calls/month. Full plan in [`campaigns/linkedin-outbound.md`](../campaigns/linkedin-outbound.md). - -## The Strategic Debate (Unresolved) - -| Path | Pros | Cons | -|---|---|---| -| **Generic horizontal SaaS** | Scales fast, no integration dependency, broad TAM | Commodity risk — many AI note-takers in market | -| **Odoo vertical specialist** | Defensible moat (200K+ Odoo partners, ~6-month competitive window), productivity-sharing pricing possible | Narrower TAM, slower expansion | - -Hassan's leaning has shifted multiple times. Current approach: run both for 90 days, let CAC and conversion data decide. - -## SEO (Deferred) - -Long-tail keywords identified ("remote team monitoring", "train remote employees", "meeting productivity tools") + AI SEO (LLM visibility optimization). Not started until paid media shows proof of concept (~6 months from launch). - -## Pricing Tiers - -Free / Basic / Pro / Business / Enterprise. Productivity-sharing model proposed for vertical Odoo path — billed against productivity gains rather than seats. - -## Source notes -- `vibe/llm-wiki/wiki/Knowcap/topics/Knowcap Marketing Strategy.md` -- `vibe/llm-wiki/wiki/Knowcap/topics/Knowcap Strategic Planning and Roadmap.md` -- `vibe/llm-wiki/wiki/Knowcap/topics/Knowcap Leadership and Fundraising Strategy.md` diff --git a/docs/strategy/june-2026-gtm-game.md b/docs/strategy/june-2026-gtm-game.md deleted file mode 100644 index 9d915f3..0000000 --- a/docs/strategy/june-2026-gtm-game.md +++ /dev/null @@ -1,193 +0,0 @@ ---- -title: "June 2026 — Knowcap GTM Game" -type: article -company: Knowcap -confidence: high -status: developing -decisions: ["[[wiki/Knowcap/decisions/2026-05-25 - Strategic Council - Vision Thesis Stress Test]]"] -sources: ["[[wiki/AV Ventures/strategies/q2-q3-2026-consolidated-plan]]"] -created: 2026-05-25 -updated: 2026-05-25 -tags: [gamification, gtm, content, marketing, sales, june-2026] ---- - -# June 2026 — Knowcap GTM Game - -> 120 hours. $2K. 22 workdays. The goal: arrive at July 1 with weekly content locked, 1 campaign running, and a pipeline of real prospects. - ---- - -## The habit that makes everything else work - -Tag 2 content-worthy moments per meeting, every meeting, starting NOW. By June 1, you'll have 10-15 tagged moments ready. Without tags, Sunday = 3-hour transcript dig. With tags = 90-minute production session. - -This is the one pre-June action that determines whether the content plan is a grind or a flow. Open Knowcap after every meeting, tag the 2 moments with the strongest hooks (real pain, real numbers, real stories), move on. 30 seconds per meeting. Compounds fast. - ---- - -## The envelope - -| Resource | Amount | Daily average | -|---|---|---| -| Hours (go-to-market only) | 120h | 5.5h/day | -| Cash | $2,000 | $91/day | -| Workdays | 22 (Sun-Thu, Jun 1-26) | -- | - -### Hour split - -| Bucket | Monthly | Daily | What counts | -|---|---|---|---| -| **Content** | 35h | 1.6h | Writing, recording, editing, posting, engaging | -| **Marketing** | 50h | 2.3h | StratDev sync, campaign setup, landing pages, positioning, creative briefs | -| **Sales** | 35h | 1.6h | Prospect research, outreach, calls, follow-ups, proposals | - ---- - -## Weekly Binary - -One question every Thursday: **Did I ship 3+ LinkedIn posts AND have 1+ sales conversation this week? Y/N.** - -That's it. No daily XP logging. No point counting. Y means the system is working. N means something broke — figure out what, fix it next week. - ---- - -## Levels (milestone-based, no XP thresholds) - -| Level | Title | You've reached it when... | -|---|---|---| -| 1 | Rookie | Starting state | -| 2 | Content Machine | 3 LinkedIn posts live + Taplio set up | -| 3 | Pipeline Builder | YouTube channel live + 1 meeting booked + 6 LinkedIn posts | -| 4 | Campaign Runner | StratDev campaign live + 3 calls done + 12 LinkedIn posts | -| 5 | Launch Ready | 1 pilot signed + 2 YouTube videos + 15 LinkedIn posts + campaign running | - -Levels are cumulative milestones, not scores. You don't lose a level. You check off the gates and move up. - ---- - -## Weekly Scorecard (Thursday EOD — the ONLY tracking mechanism) - -``` -WEEK ___ (Jun __ - __) - -CONTENT TARGET ACTUAL -LinkedIn posts published 3 ___ -Arabic LinkedIn posts 1 ___ -YouTube videos published * ___ (* starts week 3) -Engagement rounds 5 ___ - -MARKETING TARGET ACTUAL -StratDev syncs (with decisions)1 ___ -Campaign status (live/paused) ___ ___ -Analytics reviewed + actioned 1 ___ - -SALES TARGET ACTUAL -Outreach sent 5 ___ -Meetings/calls completed 1 ___ -Follow-ups sent (<24h) ___ ___ -Proposals sent ___ ___ - -WEEKLY BINARY: 3+ posts AND 1+ conversation? Y / N -LEVEL: ___ -HOURS SPENT: ___h / 27.5h target -BIGGEST WIN: ________________________ -BIGGEST MISS: ________________________ -NEXT WEEK FOCUS: ________________________ -``` - -No daily logging. This scorecard is filled once per week during the Thursday ritual. If you're tempted to track daily, stop — that energy goes into making the content instead. - ---- - -## Decision trigger - -**If 0 sales conversations by day 10, stop all content work.** Spend 3 days on direct WhatsApp outreach to the warm Odoo partner network. Content without pipeline is vanity. Resume content only after at least 1 real conversation is booked. - ---- - -## Minimum viable content fallback - -When everything burns and you can't hit the full plan, the ONE thing that survives is: **1 LinkedIn post from a meeting transcript.** That takes 37 minutes. If you can't do 37 minutes, the week is lost — flag it in Thursday review and recover next week. Never zero. - ---- - -## Week-by-week plan - -### Weekly production schedule - -| Day | Activity | Time | -|---|---|---| -| **Sunday** | Select tagged meeting segments + write 2 LinkedIn posts (1 English, 1 Arabic) | 2.5h | -| **Monday** | Write 3rd LinkedIn post + schedule all 3 in Taplio + engagement round | 1.5h | -| **Tuesday** | (Week 3+) Record YouTube screen recording — Knowcap on screen, Hassan narrating | 3-4h | -| **Wednesday** | (Week 3+) Light edit YouTube + publish + LinkedIn engagement round | 1.5h | -| **Thursday** | LinkedIn engagement round + measurement ritual (Taplio / YouTube Studio / Stripe) | 1h | - -**Weeks 1-2: ~5h/week (LinkedIn only). Weeks 3-4: ~9h/week (LinkedIn + YouTube).** - -YouTube time budget: 3-4h per video, not 2h. Month 1 = zero-production screen recordings (3-5 min, Knowcap on screen, Hassan narrating). Graduate to polished HyperFrames + B-roll in month 2 only if weekly cadence holds. - -### Week 1 (Jun 1-5) -- "First Blood" -Gates: 3 LinkedIn posts live. Taplio set up and scheduling. ONE StratDev campaign submitted (Scope Creep Insurance). -Level target: 2 (Content Machine) - -### Week 2 (Jun 8-12) -- "Pipeline Start" -Gates: 3 more LinkedIn posts (6 cumulative). First sales outreach to 5 warm contacts. Decision trigger active — if 0 conversations by Jun 10, pivot to direct outreach. -Level target: Still 2, pushing toward 3 - -### Week 3 (Jun 15-19) -- "YouTube Starts" -Gates: First YouTube video (ugly screen recording, ship it). 3 more LinkedIn posts (9 cumulative). Campaign optimizing based on first 2 weeks of data. -Level target: 3 (Pipeline Builder) - -### Week 4 (Jun 22-26) -- "Close Something" -Gates: Second YouTube video. 3 more LinkedIn posts (12+ cumulative). Thursday measurement. Target: 12+ LinkedIn, 1-2 YouTube, 1+ real conversation. -Level target: 4 (Campaign Runner) or 5 (Launch Ready) if a pilot closes - ---- - -## Monthly Grade (June 30) - -| Grade | Criteria | -|---|---| -| A | Level 5 + 1 pilot signed + 15+ LinkedIn posts + 2 YouTube videos + campaign running | -| B | Level 4 + 12+ LinkedIn posts + 1 YouTube video + 3+ calls + campaign live | -| C | Level 3 + 9+ LinkedIn posts + YouTube channel live + 1+ conversation | -| D | <9 LinkedIn posts OR no campaign submitted OR 0 conversations | - ---- - -## Anti-cheat - -The system is milestone-based (see Levels + Weekly Binary) — there is no XP. The anti-cheat is about not gaming the *milestones*: - -1. No backdating. A gate counts on the day the action actually ships. -2. No bulk-scheduling credit. 5 posts queued in Taplio = 0 published; they only count on their publish day. -3. No vanity outreach. A LinkedIn connection request is not outreach; a personalized message is. -4. No phantom meetings. "Informal chat at dinner" is not a sales conversation; a structured discovery call is. -5. Posts must be Knowcap-relevant. A meme repost does not count toward the weekly 3. - ---- - -## Measurement ritual (Thursday, 30 min) - -Open 4 tabs side by side: - -1. **Taplio** — LinkedIn post impressions, engagement rate, follower growth, best-performing posts -2. **YouTube Studio** — video views, watch time, subscriber delta, click-through rate -3. **Stripe** — new customers, MRR, churn -4. **Timely** — hours spent per bucket (content / marketing / sales) vs target - -Log the numbers in that week's scorecard. Kill/scale decision on each content track based on data. - ---- - -## Tools + monthly spend - -| Tool | Cost | Purpose | -|---|---|---| -| Taplio | $39/mo | LinkedIn scheduling + analytics + content inspiration | -| Knowcap | $0 | Meeting → content extraction (our own product) | -| HyperFrames | $0 | Motion graphics / branded intros (month 2+) | -| Higgsfield | $0 (included) | AI video generation | -| Adobe Podcast (Enhance) | $0 (free tier) | Audio cleanup | -| **Total new spend** | **$39/mo** | | diff --git a/docs/strategy/knowcap-vs-claude-division-of-labor.md b/docs/strategy/knowcap-vs-claude-division-of-labor.md deleted file mode 100644 index f5fc819..0000000 --- a/docs/strategy/knowcap-vs-claude-division-of-labor.md +++ /dev/null @@ -1,100 +0,0 @@ -# Knowcap vs. Claude — division of labor for B2B custom automations - -Hassan-owned. The forward strategy for how Knowcap and Claude/Claw split the work when we automate a B2B team's operations. Read this before scoping any "implant Knowcap, then automate the org" engagement. - -**Created:** 2026-06-08. Companion to [`../brand/STRATEGY.md`](../brand/STRATEGY.md) (the three-loop product flywheel) and [`../brand/VISION.md`](../brand/VISION.md). - ---- - -## The one line - -> **Knowcap is the data plane. Claude is the build plane. Knowcap captures, verifies, and serves the org's truth; Claude builds the bespoke automations on top of that truth. Knowcap does not need its own general-purpose AI brain — the brain for custom work is Claude.** - -A repeatable automation graduates *down* into Knowcap as a native feature. A bespoke one stays *up* in Claude. The boundary test below decides which. - ---- - -## Two planes - -| | **Knowcap — the data plane** | **Claude / Claw — the build plane** | -|---|---|---| -| **Job** | Capture every channel, classify into the commitment ontology, get a named human to verify, store as the verified graph, serve it via MCP | Build the bespoke thing the client actually needs: a website, an app, an integration, a multi-step automation | -| **Always on?** | Yes — runs continuously, ingesting and serving | No — invoked per build, episodic | -| **Owns the intelligence?** | No general-purpose brain. It runs *small, bounded* automations (notify, draft, create-task, log) and the verification gate | Yes. The reasoning, the code, the bespoke logic lives here | -| **What it is to the client** | The trusted memory + the small-automation runtime | The muscle that builds whatever is too custom to be a product feature | -| **Unit** | A verified memory; a native Skill / Vertical Pack | A delivered build (repo, deployed app, wired integration) | - -The mistake to avoid: trying to make Knowcap a do-anything agent platform that reasons its way through any custom request. That's Claude's job. Knowcap's edge is **trusted data + a tight set of native automations**, not open-ended intelligence. - ---- - -## "Knowcap doesn't need its own AI brain" — what that means precisely - -It does **not** mean Knowcap has no AI. It runs extraction, classification, edge-suggestion, and Ask-Knowcap (read-only answers). Those are **bounded** AI jobs scoped to the data plane. - -It **does** mean: when a client wants ten things automated, we do **not** try to express all ten as Knowcap-internal agents reasoning over the graph. We point Claude at the verified graph (via MCP) and Claude builds the ten things — as code, as integrations, as deployed automations. Knowcap is the source of trusted context Claude reads from and writes confirmed results back to. The heavy, bespoke reasoning is Claude's, not a feature we build into Knowcap. - -This keeps Knowcap's surface small and trustworthy and puts the open-ended work where open-ended work belongs. - ---- - -## The boundary test - -For any automation a client asks for, ask one question: - -> **"Would ten other clients want this *identical* thing?"** - -- **Yes → it's a product.** Build it once as a native Knowcap Skill or fold it into a Vertical Pack. It graduates into the data plane and every client gets it. -- **No → it's bespoke.** Claude builds it for this client on top of their verified graph. It stays in the build plane. -- **Sort-of (the shape repeats, the specifics differ) → hybrid.** Knowcap provides the native capture/verify/serve half; Claude builds the client-specific action half against the MCP. - -Three buckets, one question. Run every requested automation through it before deciding who builds it. - ---- - -## The bespoke → product flywheel - -``` -Client needs automation X - ↓ -Boundary test: bespoke → Claude builds it on the verified graph - ↓ -A 2nd, 3rd client needs the same shape - ↓ -It crosses the "10 clients want it" line → productize into a native Knowcap Skill / Vertical Pack - ↓ -Every future client gets X out of the box → services time shrinks → margin rises - ↓ - LOOP -``` - -Services revenue (Claude builds) funds the product and *discovers* which features are worth building. The product (Knowcap native) makes the next engagement faster and cheaper. This is the same shape as the Loop-3 Vertical Packs flywheel in [STRATEGY.md](../brand/STRATEGY.md) — the difference is that the *input* to the marketplace is real paid bespoke work, not guesses. - -**Rule:** don't productize on the first request. Let the boundary test fail twice (bespoke for client 1 and 2) before you spend product time. Premature productizing builds features one client wanted and nine don't. - ---- - -## The B2B engagement motion - -The repeatable shape for an org-wide engagement (the Ariika archetype): - -1. **Implant (≈30 days).** Knowcap becomes the ingestion layer across the org — meetings, recordings, uploads, URLs, text, and Telegram (the channels that capture today). Every employee's real work flows in and gets classified + verified. -2. **Capture → strategy.** From the verified graph, produce an **AI strategy** the client signs off on: here are your commitments, risks, bottlenecks, and the automations that would actually move the needle — each tagged native / hybrid / bespoke via the boundary test. -3. **Claw builds.** Claude builds the signed-off automations — bespoke ones as code/integrations, native-shaped ones as Knowcap Skills. -4. **Graduate repeatables.** Anything that recurs across clients crosses the boundary line and becomes a product feature. - -Knowcap is the always-on layer in steps 1–2 and the home for graduated features in step 4. Claude is the muscle in step 3. - ---- - -## What this means for the Knowcap roadmap - -- **Build into Knowcap (native):** capture across more channels, the verification gate, the commitment ontology, edge suggestion, Ask-Knowcap (read-only), small bounded automations (notify / draft / create-task / log), the MCP that serves verified facts, and Vertical Packs for proven repeatable workflows. -- **Do NOT build into Knowcap:** open-ended "automate anything" agents, bespoke client integrations, one-off websites/apps. Those are Claude builds against the MCP. If one recurs, *then* it earns a native feature via the boundary test. -- **The MCP is the seam.** Everything Claude builds reads verified facts (and writes confirmed results back) through the Knowcap MCP with `verification_strictness`. Keeping that seam clean is what lets the two planes stay separate and the flywheel turn. - ---- - -## Worked example - -The design-crew automation analysis for Ariika applies this exact test — 13 candidate automations sorted into native / hybrid / bespoke, with the flywheel candidates (spec-checker, call-QA) called out. See `~/Github/ariika/ai-program/boundary-test-design-crew.html` and the program overview at `~/Github/ariika/ai-program/knowcap-vs-claude-architecture.html`.