Graph RAG

Graph RAG constructs a knowledge graph from your documents — entities, relationships, attributes — and then traverses the graph at query time. This is dramatically more powerful than vector RAG for multi-hop reasoning ("what companies has Person X founded that were later acquired by Y?") because it can follow chains of relationships rather than relying on text similarity. Microsoft's GraphRAG paper popularized the pattern; LangChain, LlamaIndex, and several specialized tools support it.