AI SQL query generator

Text-to-SQL.
Plain English in, SQL out.

Describe what you want to know. Tablize generates the SQL, runs it against your live database, draws the chart, and explains the result — and it always shows you the query it wrote, so the answer is auditable, not a black box.

From a sentence to a query

You ask in plain English:

"What were my top 5 products by revenue last month, and how does that compare to the month before?"

Tablize generates and runs the SQL — and shows it to you:

SELECT p.name,
       SUM(oi.quantity * oi.unit_price) AS revenue
FROM order_items oi
JOIN products p ON p.id = oi.product_id
JOIN orders o ON o.id = oi.order_id
WHERE o.created_at >= date_trunc('month', now()) - interval '1 month'
GROUP BY p.name
ORDER BY revenue DESC
LIMIT 5;

SQL you can read and trust

01

Schema-aware

The generator reads your real tables and columns before writing a query — it doesn't guess at field names.

02

The SQL is shown

Every generated query is visible. Read it, copy it, edit it, re-run it. The number is always traceable to a query.

03

Verified, not guessed

In Deep Analysis mode the agent samples rows and sanity-checks results before giving you a figure.

Frequently asked

What is text-to-SQL?

Text-to-SQL (also called NL2SQL or natural-language to SQL) turns a plain-English question into a SQL query, runs it, and returns the answer. Tablize does this over your live PostgreSQL or MySQL database — and always shows the SQL it generated.

Is this an AI SQL query generator?

Yes. Tablize is an AI SQL generator that writes the full query from your question — joins, aggregations, window functions, CTEs — then runs it and explains the result. You can copy the SQL, edit it, and re-run it.

Does it know my schema?

Yes. The agent inspects your real tables, columns, types, and relationships before writing a query, so it uses correct field names and joins instead of hallucinating them.

How accurate is the generated SQL?

Because it reads your live schema first and shows you the query, the result is auditable. In Deep Analysis mode it also samples rows and sanity-checks the output before presenting a number.

Which databases and dialects are supported?

PostgreSQL and MySQL directly, plus Snowflake and Supabase, and 39 SaaS sources. A single plain-English question can even join across more than one of them.

How is this different from natural-language SQL?

"Text-to-SQL" and "natural-language SQL" describe the same capability. See our natural-language SQL page for the same feature framed around asking your database in English.

Stop writing SQL by hand. Start generating it.

Connect a database and get your first query — generated for you — in under a minute.