Vanna AI
Open-source RAG framework for accurate text-to-SQL generation
Overview
Vanna AI is an open-source Python framework for generating accurate SQL from natural language using retrieval-augmented generation. It trains on your schema, documentation and example queries, then produces SQL via agentic retrieval, working with any LLM provider and database. Designed to be embedded into custom applications, it is modular with no cloud-only lock-in.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 4 Jun 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
ASEAN Perspective
Vanna AI in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Vanna AI is a developer-first, embeddable text-to-SQL library rather than a full BI app, which makes it ideal for teams who want to bake natural-language querying into their own products. Its RAG approach — training on schema, docs and example queries — improves accuracy on complex databases.
With strong GitHub traction and no vendor lock-in, it is a flexible building block. Teams wanting a finished dashboard experience should look at Wren AI instead; Vanna is the toolkit, not the product.
About this listing
This entry was compiled from publicly available data including Vanna AI's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Vanna AI unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to Vanna AI directly →
Spotted something out of date? Suggest an update →
More in Research & Data
