GraphRAG: Making Enterprise Knowledge Accessible
Explore how a GraphRAG workflow connects approved documents and relationships, brings supporting passages into view, and prepares answers for human review.
Why keyword search is not enough
- Enterprise questions often require connecting people, documents, events, obligations, and outcomes. Keyword search can find matching text, but it struggles when the answer depends on relationships across records.
How GraphRAG changes retrieval
- GraphRAG combines retrieval with a knowledge graph so AI can reason across linked entities and evidence. This is useful for compliance, education, healthcare, financial review, and large document collections.
Human review remains essential
- A useful review experience shows supporting passages, source records, missing context, and uncertainty. Reviewers can check the evidence, revise the draft, or decline to use it.
Evaluate with representative questions
- Start with approved sample documents and questions whose supporting passages are known. Include questions with conflicting evidence or no answer in the source set. Review source relevance and answer quality separately, and check that access restrictions remain effective.