AI agents don’t hallucinate because the models are bad. They hallucinate because the data has no shared meaning. When agents query raw tables directly, “revenue” becomes whatever the context implies. The semantic layer fixes that: enforcing consistent metric definitions, applying security policy before any query executes, and making every agent response auditable after the fact. Daniel Gray, VP of Solution Engineering at AtScale, shows what that infrastructure looks like in production across Snowflake, Databricks, and BigQuery.