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

A team deployed a RAG-based customer support assistant relying on manual vibe checks, which failed in production. The assistant provided hallucinated responses regarding billing cycles and API rate limits, affecting over 500 users. To resolve this, the team replaced the subjective "looks good to me" approach with automated evaluation pipelines. This transition to production-grade metrics allowed them to successfully identify and catch 92% of hallucinations before the system reached the deployment stage.