Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-Augmented Generation (RAG) has become the standard methodology for grounding large language models (LLMs) in proprietary data. The typical architecture—which involves segmenting documents, embedding them into a vector database, and retrieving the top ‘k’ results using cosine similarity—is highly effective…





