text to sql

Vector search over rows is the wrong tool when the user asks for a count or an aggregate. The signal is retrieving the right schema, generating validated SQL, and knowing when to query the database instead of embedding it.

Text-to-SQL is deceptively hard because correctness is binary and the failure mode is a confident wrong number. The signal is schema grounding, query validation, and a safety layer, not just 'prompt an LLM with the schema.' Here is the production design.

'What was revenue by region last quarter?' sounds like text-to-SQL, but production analytics agents fail on ambiguity, wrong joins, and confidently wrong numbers. Here is the architecture that makes the answers trustworthy.