GraphRAG: The Definitive Guide

Chapter 8. Agentic GraphRAG

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As GenAI systems mature beyond simple question-answering into autonomous decision-making and multi-step reasoning, the demands on retrieval architectures are shifting dramatically. Static retrieval pipelines, even those augmented with knowledge graphs, hit their limits when users ask questions that require planning, decomposition, and iterative exploration of connected information.

Agentic GraphRAG combines the connected retrieval of GraphRAG with an autonomous reasoning loop, enabling the system to decompose questions, decide which tools to call, traverse the graph strategically, and synthesize results across multiple retrieval steps.

In this chapter, we follow OMG Consulting’s evolution from a static GraphRAG pipeline to a fully agentic system.

After implementing their GraphRAG pipeline, as shown in Chapter 3, OMG saw real improvements in retrieval quality. Questions about consultant skills, project histories, and client relationships were answered with much more ...