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Natural Language Data Access
Enterprise
Text-to-SQL
Building text-to-SQL that works on real enterprise warehouses — thousands of tables, messy schemas, and governance rules.
Focus areas
Schema-Aware Retrieval
Ranking the right tables, columns, and joins across large catalogs.
Semantic Layer Grounding
Queries that respect canonical metrics from dbt, Cube, or LookML.
Validation & Self-Correction
Pipelines that verify SQL before results reach the user.
Governance & Security
Row-level security, masking, and audit trails built in.
Have a warehouse
your team can't query?
Tell us about your schema and we'll show you what's possible.