Building Production-Grade LLM Evaluation Pipelines: From Vibes to Metrics

A team deployed a RAG-based customer support assistant that initially passed manual testing but failed in production. The system provided hallucinated responses regarding billing cycles and API rate limits to over 500 users, including data from competitors. To resolve this, the team replaced subjective "vibe checks" with production-grade LLM evaluation pipelines. This transition to automated metrics allowed them to identify and catch 92% of hallucinations before the assistant reached the deployment stage.