Snowflake Introduces Ontology Layer to Help AI Reason Over Business Data

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At Snowflake Summit 2026, Snowflake Chief AI Architect Taja presented a framework for building ontologies natively on Snowflake to give AI agents a structured understanding of business semantics. The core argument is that enterprise AI struggles not due to model limitations but because AI cannot interpret raw database tables as real-world business concepts like people, teams, or contracts. The proposed solution is a five-layer architecture separating physical data storage, declarative ontology metadata, auto-generated views, purpose-built semantic models, and a Cortex Agent orchestration layer. To simplify deployment of this architecture, Snowflake also unveiled the Ontology Stack Builder tool, which uses an interactive, human-in-the-loop workflow to reduce setup time from weeks to under one hour. The system is designed so that facts are stored once, semantics are defined as configuration, and AI agents route queries intelligently rather than relying on hardcoded SQL.

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