GraphRAG (Microsoft)

GraphRAG is an approach developed by Microsoft that combines knowledge graphs with RAG (Retrieval Augmented Generation) architecture. Instead of classic search for nearest chunks in vector space, GraphRAG searches the knowledge graph structure, which gives better answers to complex questions requiring information from multiple sources.

In classic RAG, the question 'What are the common side effects of cortisol and prednisone?' requires finding and combining two separate chunks, which can be unreliable. GraphRAG traverses the graph from 'cortisol' and 'prednisone' nodes to shared attributes through SHARES_ATTRIBUTE relationships — the answer is structural, not probabilistic.

In SEO context, GraphRAG is inspiration for building company chatbots and semantic search engines on client websites. GraphRAG is an advanced technique, but the concept is simple: the graph provides the STRUCTURE of knowledge, the LLM provides the LANGUAGE of the answer.

In practice, before implementing full GraphRAG, start with simple RAG enriched with graph metadata — adding relationship labels to chunks already significantly improves answer quality.