
WrenAI
⚡️ GenBI (Generative BI) queries any database in natural language, generates accurate SQL (Text-to-SQL), charts (Text-to-Chart), and AI-powered insights in seconds.
Stars: 11999

WrenAI is a data assistant tool that helps users get results and insights faster by asking questions in natural language, without writing SQL. It leverages Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) technology to enhance comprehension of internal data. Key benefits include fast onboarding, secure design, and open-source availability. WrenAI consists of three core services: Wren UI (intuitive user interface), Wren AI Service (processes queries using a vector database), and Wren Engine (platform backbone). It is currently in alpha version, with new releases planned biweekly.
README:
Wren AI is your GenBI Agent, that you can query any database with natural language → get accurate SQL(Text-to-SQL), charts(Text-to-Charts) & AI-generated insights in seconds. ⚡️
https://github.com/user-attachments/assets/f9c1cb34-5a95-4580-8890-ec9644da4160
What you get | Why it matters | |
---|---|---|
Talk to Your Data | Ask in any language → precise SQL & answers | Slash the SQL learning curve |
GenBI Insights | AI-written summaries, charts & reports | Decision-ready context in one click |
Semantic Layer | MDL models encode schema, metrics, joins | Keeps LLM outputs accurate & governed |
Embed via API | Generate queries & charts inside your apps (API Docs) | Build custom agents, SaaS features, chatbots (Streamlit Live Demo) |
Using Wren AI is super simple, you can set it up within 3 minutes, and start to interact with your data!
- Visit our Install in your local environment.
- Visit the Usage Guides to learn more about how to use Wren AI.
- Or just start with Wren AI Cloud our Managed Cloud Service. (OSS vs. Commercial Plans).
If your data source is not listed here, vote for it in our GitHub discussion thread. It will be a valuable input for us to decide on the next supported data sources.
- Athena (Trino)
- Redshift
- BigQuery
- DuckDB
- PostgreSQL
- MySQL
- Microsoft SQL Server
- ClickHouse
- Oracle
- Trino
- Snowflake
Wren AI supports integration with various Large Language Models (LLMs), including but not limited to:
- OpenAI Models
- Azure OpenAI Models
- DeepSeek Models
- Google AI Studio – Gemini Models
- Vertex AI Models (Gemini + Anthropic)
- Bedrock Models
- Anthropic API Models
- Groq Models
- Ollama Models
- Databricks Models
Check configuration examples here!
[!CAUTION] The performance of Wren AI depends significantly on the capabilities of the LLM you choose. We strongly recommend using the most powerful model available for optimal results. Using less capable models may lead to reduced performance, slower response times, or inaccurate outputs.
Visit Wren AI documentation to view the full documentation.
Subscribe our blog and Follow our LinkedIn
- Star ⭐ the repo to show support (it really helps).
- Open an issue for bugs, ideas, or discussions.
- Read Contribution Guidelines for setup & PR guidelines.
- Join 1.3k+ developers in our Discord for real-time help and roadmap previews.
- If there are any issues, please visit GitHub Issues.
- Explore our public roadmap to stay updated on upcoming features and improvements!
Please note that our Code of Conduct applies to all Wren AI community channels. Users are highly encouraged to read and adhere to them to avoid repercussions.
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