2. A Schema-RAG system using a Knowledge Graph operates differently:The AI first consults the ontology to understand the question’s components.It finds that Support Ticket is a class linked via a property referencesProduct to the Product class.It discovers that the Product class has a property called productType, and that ‘Connected Service’ is a specific instance of that type.Armed with this understanding of the relationships, it constructs a precise, formal query (SPARQL) to retrieve only the tickets that conform to this logic.

Knowledge Graphs provide the semantic context, constraints and explicit relationships that LLMs lack. This enables true reasoning, like navigating a map of your business, instead of just text retrieval.

Standard Retrieval-Augmented Generation (RAG) over documents is a good first step, but it fails when faced with complex, cross-domain enterprise questions. It finds text that looks similar, which isn’t the same as finding facts that are related.