Category: RAG Infrastructure

It was 11:23 p.m. on a Tuesday when a $12.2 million trading loss hit a bulge-bracket bank’s risk desk. The culprit wasn’t a rogue trader or a faulty model. It was a retrieval step that had been removed at the CTO’s insistence. Six months earlier, the firm had decommissioned its retrieval augmented generation (RAG) pipeline,…

Your enterprise RAG system retrieves documents flawlessly. It returns precise answers from your knowledge base. Your retrieval metrics look solid. Then someone asks about the diagram in last quarter’s engineering review. Or wants to analyze customer service call recordings. Or needs insights from product demo videos. Your RAG system goes silent. This isn’t a failure…

This comprehensive article discusses the critical gap in retrieval quality evaluation within enterprise RAG systems. It introduces a three-layer evaluation framework—query-level, corpus-level, and attribution metrics—and outlines an 8-week plan to implement continuous monitoring. Emphasizing the importance of metrics like Recall@K, MRR, and NDCG, it provides practical guidance to build a measurement infrastructure that ensures retrieval…