A concrete example
Question: 'which clients contacted which sales reps last week?'. GraphRAG follows the links; a classic RAG gets lost.
Why it matters
GraphRAG shines on questions about relationships between entities. For plain text, vector RAG is often still better.
You run into it in Microsoft GraphRAG, knowledge graphs, and analyses of large document corpora.
Don't mix it up with
RAG: RAG lets an AI answer using documents pulled up at the moment you ask the question.
Knowledge graph: A knowledge graph links entities together to represent who is connected to what across a corpus.
Common mistakes
- Wanting GraphRAG everywhere with no graph built behind it.
- Mixing up GraphRAG and knowledge graph (the second is a prerequisite for the first).
- Underestimating the cost of building the graph.
Quick checklist
- First I check whether the word names a concept, a tool, a risk, or a metric.
- I tie it to a concrete case: Question: 'which clients contacted which sales reps last week?'. GraphRAG follows the links; a classic RAG gets lost.
- I keep the main trap in mind: Wanting GraphRAG everywhere with no graph built behind it.
Quick questions
What is GraphRAG in AI?
GraphRAG adds a graph of relationships to answer questions that need a big-picture view.
Where will I run into GraphRAG?
You run into it in Microsoft GraphRAG, knowledge graphs, and analyses of large document corpora.
Which word should I read next?
Start with RAG, Knowledge graph, Agentic RAG.