Graph RAG enhances AI answers by mapping relationships

A new approach called Graph RAG helps AI systems answer complex questions by explicitly mapping connections between pieces of information, rather than relying on document similarity alone. Where traditional vector search finds relevant records based on how closely their wording matches the question, Graph RAG draws relationships—so it can tell, for example, which customers are affected by a software bug that traces through layers of dependencies. It’s heavier to set up, but necessary when answers depend on connecting the dots.

• Graph RAG links facts via explicit relationships
• Traditional vector search only finds similar-sounding records
• Graph RAG clarifies ownership, dependencies, and affected parties
• It’s most needed when business context requires pinpointing connections