Amazon Neptune now supports BYOKG - RAG (GA) with open-source GraphRAG toolkit

Today, we are announcing the support of Bring Your Own Knowledge Graph (BYOKG) for Retrieval-Augmented Generation (RAG) using the open-source GraphRAG Toolkit. This new capability allows customers to connect their existing knowledge graphs to large language models (LLMs), enabling Generative AI applications that deliver more accurate, context-rich, and explainable responses grounded in trusted, structured data.

Previously, customers who wanted to use their own curated graphs for RAG had to build custom pipelines and retrieval logic to integrate graph queries into generative AI workflows. With BYOKG support, developers can now directly leverage their domain-specific graphs, such as those stored in Amazon Neptune Database or Neptune Analytics, through the GraphRAG Toolkit. This makes it easier to operationalize graph-aware RAG, reducing hallucinations and improving reasoning over multi-hop and temporal relationships. For example, a fraud investigation assistant can query a financial services company’s knowledge graph to surface suspicious transaction patterns and provide analysts with contextual explanations. Similarly, a telecom operations chatbot can detect that a series of linked cell towers are consistently failing, trace the dependency paths to affected network switches, and then guide technicians using SOP documents on how to resolve the issue. Developers simply configure the GraphRAG Toolkit with their existing graph data source, and it will orchestrate retrieval strategies that use graph queries alongside vector search to enhance generative AI outputs.

To learn more and get started, visit the GraphRAG Toolkit User Guide.