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 billing policies and incorrect API rate limits from competitors, affecting over 500 users. To resolve this, the team replaced subjective testing with production-grade LLM evaluation pipelines. This transition to automated metrics allowed them to identify and catch 92% of hallucinations before deployment, ensuring higher accuracy and reliability for their customer-facing AI system.