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Turn natural language into SQL across databases with document QA and semantic caching.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "NLQueries" yet — see the docs or source repo.
Connect to my PostgreSQL and BigQuery sources, query "new users and conversion rates by channel in the last 90 days" in natural language, and generate the corresponding SQL.
Executable SQL, a summary of the query results, and key metrics organized by channel.
Read the product metrics documentation and table schemas, answer the definition of "active users," and provide a SQL query to calculate monthly active users.
A document-grounded explanation of the metric definition plus a SQL example aligned with that definition.
Enable semantic caching for common sales analysis questions so that when users ask similar monthly sales trend questions repeatedly, existing results are reused first and cache hits are indicated.
Query results with cache-hit indicators, reducing repeated SQL generation and execution time.
Query SQL databases in natural language with auto-generated, self-correcting SQL.
Turn natural language questions into SQL and run them on SQLite databases.
Convert plain English into SQL and interactively inspect and query databases.
Query MSSQL databases safely in natural language with schema discovery.
Turn natural-language questions into validated read-only SQL for SQLite queries.
Query any SQL database in natural language with safe auto-generated SQL.