Ask in English.
Get production SQL.
Dialect routes your question through nine specialized agents - intent, context, schema, planner, writer, validator - before any LLM writes a line of SQL.
-- validated · schema-safe SELECT d.market, AVG(b.balance) AS avg_deposit FROM deposits b JOIN dim_market d ON b.market_id = d.id WHERE b.period_end BETWEEN '2026-10-01' AND '2026-12-31' GROUP BY d.market ORDER BY avg_deposit DESC;
Nine agents.
One question.
Banking semantic layer
Domain-specific table descriptions, column relationships, and business glossary baked into every plan.
Context reranking
Candidate tables and fields are scored by relevance, with dimensional modeling preferences applied.
Self-correcting SQL
Validation failures trigger an automatic repair loop. Schema errors are fixed before you see them.
Explainable plans
Every query comes with a step-by-step breakdown of what it does and why each join was chosen.
Ask. Enrich. Execute.
Ask in plain English
Type "Show average deposit balance by market for Q4". Intent is classified instantly.
Multi-agent pipeline
Nine agents collaborate to fetch context, rank fields, plan structure, and validate SQL.
Execute & visualize
Run against live banking data. Explore results in interactive tables and charts.
The best prompt
is richer context.
Dialect ships with the banking semantic layer. Plug in your schema, get answers.