Tag: rag

Evidence-based analysis of GraphRAG's failure modes — benchmarks where it underperforms vanilla RAG — with concrete mitigations and scenarios where graph-based retrieval dominates.

How LazyGraphRAG collapses GraphRAG indexing costs from $30,000 to $30 by deferring entity extraction to query time — with a practical guide to when lazy beats eager.

How knowledge graphs solve the structural context gap that vector databases leave open — GraphRAG architecture with Cypher traversal patterns and LLM context serialization.

GraphRAG enhances retrieval-augmented generation by grounding LLM responses in structured knowledge graphs instead of flat vector embeddings.

The fastest-growing CNCF category — ML serving, vector databases, and the open AI stack running on Kubernetes.

Comprehensive guide on training artificial intelligence for software testing: architectures, pedagogical strategies, and validation frameworks