Google has made LookML indexing in Knowledge Catalog generally available for Looker Core on Google Cloud. The product separates two kinds of context. Knowledge Catalog supplies asset discovery, lineage, governance tags and policy documents; LookML supplies SQL formulas, join paths, filters and aggregation rules for business metrics.
That distinction targets two specific text-to-SQL failures. Metric-definition drift lets “revenue” or “exposure” mean different things in different queries. One-to-many join fan-out can multiply rows and inflate a total. The integration indexes resolved models, Explores, Views, fields, dashboards and lineage, including join conditions, relationship cardinality, required joins, filters, primary keys and compiled SQL expressions.
Google says updates synchronize into Knowledge Catalog in near real time. Gemini Enterprise can retrieve the context through built-in read-only access; custom agents can request it through the LookupContext API. The agent still generates SQL through its connector. The semantic layer supplies definitions and join logic; it does not guarantee that every query is correct. No independent accuracy, latency, token-savings or cross-platform study is published. Google Cloud.