Vanna AI
vanna.ai
AI-powered SQL agent that generates queries from natural language questions
Description
The SQL Agent · Build AI agents that ship to production. User-scoped execution, rich UI components, and quota management built-in. · Choose Your Stack
anna AI is an open-source Python-based AI SQL agent designed to write complex SQL queries in seconds. It allows users to ask data questions in plain English, translating them into SQL for various databases like Snowflake, BigQuery, and PostgreSQL. Vanna AI trains on specific database schemas, ensuring high accuracy for complex datasets, and continuously improves through user interactions
Features
Natural language to SQL conversion
database-specific training
support for multiple databases
continuous learning
customizable deployment
Use cases
Data analysis, database management
business intelligence
developer productivity enhancement
secure data querying
FAQ
Vanna AI is an AI-powered tool that enables users to query databases in plain English, automatically generating accurate SQL queries without requiring SQL coding skills. It serves business users, data analysts, and developers by transforming natural language questions into executable SQL queries to retrieve data insights.
Vanna AI is for business users who need quick answers from data without deep technical skills, data analysts wanting faster query generation, and developers embedding AI-powered querying in applications.
Vanna AI works through several steps: first, it is trained on your database schema, documentation, SQL examples, and metadata using a retrieval-augmented generation (RAG) method. Then, users provide natural language questions, which Vanna converts into SQL queries using large language models (LLMs) and executes against the connected database. Lastly, it features self-learning, improving over time by learning from successful question-query pairs and feedback.
Vanna AI supports various popular databases like Snowflake, BigQuery, Postgres, Azure SQL, and more out-of-the-box with customizable connectors.
Vanna 2.0 provides features such as user-scoped execution with permissions and rate limits, interactive rich UI components like charts and tables, integration with LLM providers including OpenAI GPT and Anthropic Claude, audit logs, observability, quota management, and support for embedding within applications or web components.
Vanna AI handles security and privacy by supporting multiple deployment models, including on-premises, self-hosted open source, or cloud-hosted. It uses Role-Based Access Control (RBAC) with group-based permissions and sends only user questions, prompts, execution results, and conversation context to LLM providers, not raw database content by default. Additionally, it offers comprehensive audit logging with sanitized parameters for compliance and enforces user identity and access control on every request and tool usage.
Yes, Vanna AI offers flexible integration via web components, Jupyter notebooks, Slackbots, Streamlit apps, and custom frontends. Developers can customize database connectors and user data context handling.
Vanna AI is improved over time as it saves successful interactions in its Tool Memory, allowing it to reference past queries and tool usages to better handle repeated or similar questions, learning database schemas and business logic without manual retraining.
Yes, Vanna.ai is open-source with documentation, example code, and a GitHub community for discussions and support.
Specs
| Type | Agent |
| Section | Data & analytics |
| Pricing | has a free tier (от $50/mo) |
| Platform | Command line |
| Systems | cli, web |
| Who for | Individual |
| Site language | en |
| Rating | 0.00 (0 reviews) |
| Views | 40 406 |
| Launched | 2024-07-25 |
