When Vectors Break Down: Graph-Based RAG for Dense Enterprise Knowledge - Sam Julien, Writer
Jul 22, 2025 · 15:47
Sam Julien, Director of Developer Relations at Writer, explains how the company built a graph-based RAG system that achieved 86.31% accuracy on the RobustQA benchmark and sub-second response times, significantly outperforming vector search approaches for dense enterprise knowledge. The team moved from simple vector retrieval to a graph-based approach to handle concentrated data where similar terms appear frequently, solving problems like inaccurate chunking and failure with similar documents. They built a specialized model to convert data into graph structures, stored as JSON in a Lucene-based search engine, and incorporated Fusion-in-Decoder with knowledge graphs to lower hallucination rates. Key decisions included focusing on customer needs over hype, staying flexible based on team expertise, and letting research challenge assumptions, leading to features like multi-hop reasoning and complex data format handling.
