WrenAI is your AI data assistant that helps you get results and insights faster by asking questions without writing SQL.
WrenAI is reimagining how businesses can interact with and leverage their data through LLM, by bringing comprehension capabilities to small and large data teams.
👉 Learn more about our mission
WrenAI offers detailed, explainable responses, ensuring users understand the origins and context of their data, thereby reducing hallucinations in LLMs.
WrenAI enriches LLMs with your specific business context, with additional metadata for your data schema, such as semantics and relationships.
WrenAI evolves with every interaction. It learns from user feedback and behavioral patterns, continuously refining its suggestions.
WrenAI leverages Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) technology to enhance comprehension of internal data. Below are the three key benefits:
Discover and analyze your data with our user interface. Suitable for data analysts, and non-technical users to use.
Your database contents will never be transmitted to the LLM. Only metadata, like schemas, documentation, and queries, will be used in semantic search.
Deploy WrenAI anywhere you like on your own data, LLM APIs, and environment, it's free.
WrenAI is consist of three core services:
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Wren UI: An intuitive user interface for asking questions, defining data relationships, and integrating data sources within WrenAI's framework.
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Wren AI Service: Processes queries using a vector database for context retrieval, guiding LLMs to produce precise SQL outputs.
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Wren Engine: Serves as the semantic engine, mapping business terms to data sources, defining relationships, and incorporating predefined calculations and aggregations.
- Top 4 Challenges using RAG with LLMs to Query Database (Text-to-SQL) and how to solve it.
- How do you use LangChain to build a Text-to-SQL solution? What are the challenges? How to solve it?
We have some core design philosophies that were used when developing WrenAI.
- Explainability: WrenAI ensures that every SQL query generated in natural language is accurate, concise, and reliable.
- Interoperability: WrenAI enables users to query data from multiple sources without dealing with the complexities of different data formats and dialects, providing a standard interface across different sources.
- Interactive Experience: WrenAI is designed to engage users in a dialogue, clarifying their queries and refining results in real time.
- Continuous Learning: WrenAI will proactively learn through ongoing query history, feedback, and interactions. Incorporating new patterns, information, and data structures into our LLM knowledge base.
WrenAI is currently in alpha version. The project team is actively working on progress and aiming to release new versions at least biweekly.
Using WrenAI is super simple, you can setup within 3 minutes, and start to interact with your own data!
- Visit our Installation Guide of WrenAI.
- Visit the Usage Guides to learn more about how to use WrenAI.
Visit WrenAI documentation to view the full documentation.
- Welcome to our Discord server to give us feedback!
- If there is any issues, please visit GitHub Issues.
Do note that our Code of Conduct applies to all WrenAI community channels. Users are highly encouraged to read and adhere to them to avoid repercussions.
