SQL Query Generation AI Agent
Translate natural language to complex SQL queries across diverse enterprise databases.
Technical Capability Matrix
- Designation
- SQL Query Generation AI Agent
- Latency
- < 500ms Execution
- Security
- SOC2 / Air-Gapped
- Governance
- Policy-as-Code
Autonomous Operation Workflow
- Connect a database — a read replica or warehouse rather than production.
- Import the schema so the agent works from your real tables and keys.
- Describe any tables whose names do not explain themselves.
- Set permissions: which schemas are visible, and whether writes are possible at all.
- Ask in plain language and review the generated SQL before it runs.
- Save the queries that were right so the next person does not ask again.
Frequently Asked Questions
Will it write queries against our production database?
Only if you connect it to one, and we would not start there. The agent reads your schema and generates SQL; where that SQL runs is a connection decision you make. Most teams point it at a read replica or warehouse first and keep it read-only until they trust what it writes.
How does it handle tables whose names mean nothing?
It reads schema, keys and relationships, which carries further than people expect. Where a name is genuinely opaque — a table called DIM_T04 — it needs one line describing what that table holds. You write that once, it is stored with the connection, and every query afterwards is better for it.
What stops it inventing a column that does not exist?
Your schema is supplied as context rather than recalled from memory, so an invented column usually fails at generation rather than at execution. Queries come back for review before they run, and one that will not parse against your schema is caught before anyone sees a number.
Can it join across separate systems?
Across databases in one warehouse, yes. Across genuinely separate systems it depends on whether a join key exists. If your CRM and your ledger share no reliable identifier, no agent can invent one — that is a data problem before it is a query problem, and we will say so rather than return something that looks right.
Who is this for?
People who know the business question but not SQL, and who currently wait in a queue for someone who does. It does not replace analysts. It removes the routine pulls so analysts spend their time on the work that actually needed them.
What happens to the queries it writes?
They are kept. A question asked once becomes a query anyone can rerun, and over time that library of your organisation's real questions is worth more than any single answer it produced.