Is Licensing Required for Using Self-Hosted Wrena AI for Internal Teams

[vimox-shah-genea]

Hello,

We are considering using Wrena AI as a self-hosted solution for our internal development team. Our goal is to leverage it exclusively for internal purposes, without offering it as a service or distributing it externally.

Is it possible to use Wrena AI freely in this scenario, or are there any licensing requirements we need to be aware of or purchase for this usage? Any clarification on the terms or guidelines for self-hosted deployment would be greatly appreciated.

Thank you!

[wwwy3y3]

Hi @vimox-shah-genea,

Yes, using Wren AI as a self-hosted solution for your internal development team is free and covered under our open-source license.

For self-hosted deployment, the simplest way is to use a single VM, install Docker Compose, and launch it through our launcher. You can find detailed instructions here: https://docs.getwren.ai/oss/installation.

You could also consider our cloud version. The differences between the self-hosted and cloud options are outlined here: https://docs.getwren.ai/cloud/cloud_vs_self_host.

Let me know if you have any questions! 😊

[vimox-shah-genea]

Got it. Could you clarify the differences between Vanna AI and Wren AI? We’re exploring options for our internal development team. We’ve already tested Vanna AI, and it’s working well and it is having open-source nature and MIT License. How does Wren AI compare, and what unique benefits could it bring to our enterprise setup over Vanna AI?

[wwwy3y3]

Certainly, here are the key distinctions between Wren AI and Vanna AI:

Product Focus

Vanna AI primarily designed for Python developers, Vanna AI offers a Python-based RAG framework suitable for building text-to-SQL solutions from the ground up.
Meanwhile, Wren AI aimed at both technical and non-technical users, Wren AI provides a turnkey solution with an intuitive user interface, enabling easy installation and deployment. Beyond text-to-SQL capabilities, it offers features like generating natural language responses or insights, and a SQL breakdown feature for transparency in SQL generation.
Check out our document: https://docs.getwren.ai/oss/guide/home/answer

Semantic Layer and Design

Wren AI Incorporates the Wren Engine, a semantic engine that provides a semantic layer to large language models (LLMs). This enables LLMs to comprehend data schemas, metadata, calculation methods, and metric definitions, facilitating accurate SQL generation and data interpretation.
Details: https://getwren.ai/post/how-we-design-our-semantic-engine-for-llms-the-backbone-of-the-semantic-layer-for-llm-architecture