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AI agent

Text-to-SQL Analyst

Ask a question in English, get the query and the answer

by Raghav Menon

No measured runs yet. Metrics appear here once the evaluation engine has real execution data — they are never supplied by the seller.

What it does

Connects to your warehouse read-replica, reads the schema and answers questions in plain language. Shows the SQL it wrote before it runs, so an analyst can check the join before trusting the number.

Refuses to write anything but SELECT. It is pointed at a read replica and it has no credentials that could change a row — the safety is in the connection, not in a prompt asking it politely.

Ideal use cases

  • Operational questions against a modelled warehouse
  • Teams where non-analysts need self-serve numbers
  • Read replicas with a documented schema

Where not to use it

  • Undocumented schemas with ambiguous column names
  • Anything where a wrong number is worse than no number

The problem it solves

Every question that needs a number goes through the two people who know the schema, and they spend their week writing queries instead of doing analysis.

Details

Domain
Data & Analytics
Category
Database & ETL
Sub-category
Text-to-SQL
Architecture
Single-Agent Executor
Built for
Cross-Industry (Horizontal)
Runs on
Web + mobile
Protocols
Model Context Protocol (MCP)REST API
Ecosystems
LangChain
Deployment
Docker ContainerSlack