Canonical: https://instain.ru/en/ai/vanna/ Language: en Vanna AI Platform # Vanna. Natural language queries with user permissions and example memory 4.33 / 5 [Directory score](https://instain.ru/en/ai/vanna/#editorial-rating) [Official website ](https://vanna.ai/) Vanna connects a language model to a database to prepare SQL queries. ![Vanna: official page describing features and workflows.](https://instain.ru/assets/images/vanna-screen-451592eea3e8-1200.webp) Official Vanna page. [Open the source ](https://vanna.ai/) ## Between a question and a table Vanna connects a language model to a database and query execution tools. A user asks a question in ordinary language, and a configured agent selects the actions. Current documentation gives particular attention to user identity, permissions and memory of successful interactions. These matter more than one impressive text to SQL demonstration. The agent needs the data structure and the meaning of business fields. Columns with the same name in different tables can represent different events. Without this preparation, a plausible query can return a formally valid but misleading total. A table of results does not establish that the answer matches the question. ## A practice task with restricted permissions Prepare a small order database without personal information. Give the agent a read only connection and ask for order counts by month. Define which statuses count as an order and which date to use before running it. Compare the result with your own control query. Try a month with no records, duplicate rows after joining tables and an order whose status changed. These cases reveal whether the agent understood the structure. Saving a successful example can help later queries, but a wrong example can also persist. Check selection criteria and units before reuse. ## One question can count different things Suppose orders and order items are stored in separate tables. After a join, one order may appear several times. Counting rows then counts items, although the person asked for orders. The question sounds natural and the query runs without error, yet the result means something different. Define business terms before using an analytical assistant: what counts as a sale, which date applies and how canceled records are handled. Control examples should show the query as well as the final number. This can reveal an error before the agent reuses the example. ## Deployment and usage terms Vanna offers an open framework for running your own deployment and cloud administration features. The documentation covers different database systems and language model providers. Hosting the application locally does not automatically make model inference local: the question and available context may go to the selected provider. Paid plans cover administrative features, queries and enterprise support. Budget separately for the connected model and your database. For production data, establish who can see queries, where memory is stored and how each user’s permissions are checked. Start with reading; add modification only for a specific verified workflow with a separate confirmation step. ## Suitable tasks - Create a database assistant for questions - Prepare and verify SQL queries - Manage user rights of analytical agent Features ## Strengths - Connect questions, SQL tools and access permissions - Self hosting and support for different database systems Things to consider ## Limitations - Requires a data schema and secure connection - A plausible query can still produce an incorrect count ## Selection and conditions Free access Not confirmed Trial period Not confirmed No sign-up required Not confirmed Russian interface Not confirmed Local installation Yes API Yes “Not confirmed” means there is not enough information. The feature may still be available; check the developer’s terms. Input formats Text, Data Result Code, Data ### Terms Self hosting does not make the selected model local. Database permissions and schema details are needed; cloud administration, model calls and infrastructure have separate costs. From task to first result ## Practical example Task Create a database assistant for questions What to prepare A practice database without personal information and a question about its contents. ### Task brief or prompt Task for a configured agent: show monthly order counts from the practice database. First check the tables and field meanings, then prepare a read only query. Do not modify records; compare the result with an independent control query. ### Expected result A query and answer from the practice database with verifiable selection criteria. ### How to check the result - Check JOINs, filters, dates and duplicate counting. - Use the least permissions needed; do not invent a value when a row is absent. An editorial teaching example of a task brief, not the result of hands-on testing of the service. Check that the required mode is available, that you have rights to the source material and that the intended use of the result is permitted. Check details ## Official sources - [Official product page ](https://vanna.ai/) - [Official documentation and conditions ](https://vanna.ai/docs) - [Hosting and administration terms ](https://vanna.ai/pricing) This description is based on the developer’s material. Features, prices and availability may change; check the primary source before use. About the tool Developer Vanna AI Category [Code](https://instain.ru/en/category/code/) Access Run the open framework in your own environment; cloud and administrative features have separate access terms. Payment Self hosting is available; administration plans, cloud services, models and infrastructure are paid under their own terms. API Yes, from the developer [Developer terms ](https://vanna.ai/pricing) Directory score 4.33 / 5 Features 4.40 / 5 Workflows 4.10 / 5 Ecosystem 4.40 / 5 Documentation 4.40 / 5 Scores are an editorial guide to the directory. They are not user reviews or the results of personal testing. [See the methodology ](https://instain.ru/en/methodology/) Keep exploring ## For similar tasks [Full category ](https://instain.ru/en/category/code/) Code ### [Databricks Genie Agents](https://instain.ru/en/ai/databricks-genie/) Ask questions in plain language about curated Unity Catalog data 4.35 / 5 Data Requests Agents Similar tasks; compare terms, formats and limitations