Category: RAG Evaluation

Imagine deploying a RAG system that feels like it’s working perfectly—your LLM generates coherent responses, your retrieval returns relevant documents, and your team ships it to production confident in the outcome. Six months later, you discover a silent degradation: retrieval precision has dropped 15%, hallucination rates are climbing, and your users are quietly getting worse…