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Ontology RAG leverages rigid, predefined schemas to guide agentic reasoning and data retrieval. This ensures your agents operate within a well-defined conceptual boundary.

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Grounding agents in ontologies

By using discover-schema, your agent can introspect the available classes and properties of a world before attempting to query it.
  1. Discovery: Agent retrieves the world’s ontology.
  2. Mapping: Agent maps the user’s natural language request to specific RDF classes and predicates.
  3. Querying: Agent executes precise SPARQL queries instead of depending solely on vector similarity.

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Why use Ontology RAG?

  • Zero Hallucination: Agents only use terms that actually exist in the world’s schema.
  • Complex Logic: Handle transitive relationships and inverse properties that are invisible to vector searches.
  • Deterministic Reliability: Ensure the agent’s mental model matches the actual data structure.