GraphRAG: Knowledge Graphs for Enhanced Retrieval
Microsoft’s GraphRAG uses knowledge graphs to provide deeper context and better reasoning for RAG systems.
Standard RAG systems rely on simple vector similarity, which often fails for complex, global queries. GraphRAG, developed by Microsoft, combines the power of LLMs with Knowledge Graphs to provide a more holistic understanding of your data.
Structural Reasoning
By extracting entities and relationships from your documents and organizing them into a graph, GraphRAG allows the AI to reason about connections that aren't immediately obvious in raw text. This is particularly powerful for analyzing large collections of documents where the context is spread across many pages.
Global and Local Context
GraphRAG provides both "global" summaries of the entire dataset and "local" answers to specific questions. This dual approach ensures that the AI doesn't lose sight of the "big picture" while still being able to dive into the granular details of your private data.