Enables agents to answer analytics questions with provable correctness by resolving metrics through the semantic layer, tracing lineage, traversing knowledge graphs, checking freshness, and searching glossary definitions, while enforcing access controls and logging every call.
Enables agents to interact with a governed semantic layer for querying and authoring metrics, providing tools for discovery, planning, validation, and execution of analytics queries.
Exposes a governed semantic layer to AI agents so they select metrics and dimensions from a closed, engineer-declared vocabulary instead of writing SQL. Validates every typed call against the contract, rejects out-of-contract requests with structured errors and suggestions, and returns query rows together with the compiled SQL and dbt lineage for auditing.
Exposes a governed semantic layer built on dbt Core and DuckDB, enabling AI agents to query predefined metric definitions for a P&C insurance dataset. Prevents metric hallucination by restricting agents to governed tools and read-only data access.
Enables agents to query curated metrics through a registry-backed semantic layer, preventing ad-hoc SQL and enforcing consistent definitions. Every numeric claim is verified against the underlying query result before it is allowed to be sent.