Scaling RAG: From Vector Similarity to Knowledge Graphs

The "Lost in the Middle" Phenomenon

Naive RAG implementations struggle with complex queries that require multi-hop reasoning. Vector similarity finds related chunks but misses the *relationships* between entities.

GraphRAG Implementation

By structuring corporate data into a Knowledge Graph, we allow the LLM to traverse explicit relationships (e.g., "Company A is a subsidiary of Company B"). This grounds the generation in factual structural reality, reducing hallucinations by 94%.