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

A team deployed a RAG-based customer support assistant that initially passed manual testing through 'vibe checks'. However, 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 'looks good to me' approach with automated evaluation pipelines. This transition to production-grade metrics allowed them to successfully catch 92% of hallucinations before deployment, ensuring higher accuracy and reliability for their users.