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Mini-Me Chatbot Builder - Project Summary

The Mini-Me Chatbot Builder, developed for Rallio, represents a significant advancement in the field of SaaS AI Chatbot Platforms for consumer-oriented Network Marketing brands. Delivered in December 2023, I played a pivotal role in leading the development of this innovative product. The platform is designed to empower sales representatives from consumer product companies to create bespoke chatbots using their own custom knowledge bases, thereby facilitating more effective communication with end customers and potential business partners.

This summary summarizes my contributions to the project, highlighting the technological innovations and the collaborative effort that went into its successful delivery.

Screenshots

Project Features

Here are some of the key features of this project:

  • Voice AI Calling: Integrated a voice calling system using Bland.ai to allow prospects to interact with the chatbot through voice calls.
  • Custom Knowledge Base: Developed a feature allowing sales reps to upload their unique knowledge base documents for the chatbot to use in answering queries.
  • Custom Chatbot per Sales Rep: Enabled sales reps to create personalized chatbots, reflecting their style and preferences.
  • Visitor Database with Chat History: Included a visitor database feature to track anonymous web visitors and their chat history with the chatbot.
  • Authentication for Sales Reps: Implemented an authentication system for sales reps, ensuring secure and personalized access to the chatbot configuration and dashboard.

Technical Contributions

Here are some of my key technical contributions to this project:

  • Rapid Prototype and Backend Integration: A key achievement in the project was the development of a rapid prototype that seamlessly integrated a knowledge base and a Large Language Model (LLM), aligning closely with project specifications. This ensured that the backend performance matched the expectations set by our example applications.
  • Front-End Development: Utilizing Vercel's NextJS AI Chatbot template, I led the team in establishing the essential front-end functionality. This step was crucial in laying down the foundational user interface for the chatbot platform.
  • Integration Focus: A major focus of my role was the integration of the front-end with the backend LLM and knowledge base, including deploying the backend as an API. This was integral to ensuring the functionality of the chatbot for its specified use case.
  • Representative Customization: I contributed to tailoring the chatbot’s tone and responses by integrating detailed information about the sales representatives, a crucial aspect to mimic their style and enhance user interaction.
  • Future Development Plans: I was involved in planning for the next phases of the project, which included developing the interface and backend capabilities for launching diverse chatbots under different URL slugs, and subsequently, the homepage.

Technologies

In this project, I spearheaded the architecture and development, strategically selecting and leveraging appropriate technologies to align with our specific needs:

Cloud Services / Hosting

  • Vercel: Deployed as the hosting platform for the project. It offered scalability and ease of use, allowing for seamless integration with Next.JS and continuous deployment from our Github repositories.

AI

  • Langchain JS: Leveraged to handle interactions with the vectorstore in Postgres, allowing us to pull context from the vector store given the user's message, and embed that in a custom prompt that we send to the LLM.
  • OpenAI - GPT4: The core AI engine powering the chatbot. GPT4 provided the advanced natural language understanding and generation capabilities, enabling the chatbot to deliver informative and contextually relevant responses.
  • Bland: Integrated for the voice calling feature, allowing users to interact with the chatbot via voice calls. Bland.ai's API facilitated seamless connection between the chatbot and the voice calling system.

Application Development

  • Next.JS AI Chatbot: A framework used for building the user interface of the chatbot. It provided a starting point for our custom front-end development, facilitating rapid prototyping and efficient integration with backend services.
  • Next.JS: Utilized for its server-side rendering capabilities, enhancing the performance and SEO of the chatbot's web pages. It was instrumental in developing a responsive and dynamic user experience.
  • Postgres: Chosen as the database solution for its robustness and reliability. Used for storing and managing the chatbot's data, including user profile information and the vectorstore data.
  • Vercel KV - Redis: Chosen as the key-value storage solution for storing user sessions and chat histories.
  • React: A key technology for building the chatbot's interactive user interfaces. React's component-based architecture made it easier to manage and update the UI dynamically.
  • Typescript/Javascript: Employed as the primary programming languages for both front-end and back-end development. They provided the necessary flexibility and efficiency for building complex web applications and integrating various APIs, including those for AI and database interactions.
  • Github: Utilized for version control and collaboration among the development team. It was essential for tracking changes, managing codebases, and facilitating continuous integration and deployment processes.

Communication and Leadership

During the Mini-Me Chatbot Builder project for Rallio, my role in communication and leadership was crucial and significantly contributed to the project's success. Key contributions included:

  • Project Management: Led a team of four developers, coordinating tasks, pull requests, code reviews, and testing to maintain project momentum and quality.

  • Technical Architecture: Architected the system and authored the Product Requirements Document (PRD), reviewed with stakeholders and developers for a solid plan and approach, followed by task breakdowns and implementation strategizing.

  • Daily Communication: Ensured consistent daily communication with the team, maintaining a clear understanding of project objectives and progress, thus aligning efforts and keeping all members informed and focused.

  • Regular Update Schedule: Established a three-day update cycle for thorough project monitoring and stakeholder information relay, enabling timely feedback and adjustments.

  • Strategic Meetings and Discussions: Participated in key meetings, addressing critical aspects such as login strategies, bot personalization, and demo setups, pivotal in decision-making and project tailoring for the target audience.

  • In-depth Analysis and Requirements Gathering: Conducted thorough analysis and revisited call notes for precise project requirements understanding, aligning the project with its goals and user expectations.

  • Collaborative Planning and Implementation: Actively collaborated in planning and implementing core features like voice AI calling, custom knowledge base, and sales rep authentication, ensuring efficient execution in line with the project's vision.

In summary, my communication and leadership were integral to the effective management and successful delivery of the Mini-Me Chatbot Builder project, ensuring seamless integration of all project aspects with the strategic goals.