The Construction Bottleneck Problem
GraphRAG adoption is limited primarily by the cost of building the knowledge graph, not by query-time performance.
Most GraphRAG systems rely on LLM-based entity and relation extraction. At enterprise scale, thousands of documents, continuous updates, this becomes prohibitively expensive. Query-time optimizations are solving the wrong problem when the upstream construction cost makes the system impractical to deploy.
The pattern: teams build impressive demos on small corpora, then hit a wall when scaling to production. The impressive retrieval capabilities never materialize because they can’t afford to build the graph in the first place.
Related: 05-atom—the-94-percent-threshold, 06-molecule—dual-extraction-architecture, 05-atom—demos-deployment-ethics-gap