Evals

A comprehensive guide to evaluating large language models, covering fundamental metrics, open-ended evaluation techniques, LLM-as-a-Judge approaches, and practical guidance for implementing robust evaluation pipelines in real-world AI applications.

Discover the RAG Triad framework - a systematic approach to evaluating RAG systems through three key pillars: context relevance, groundedness, and answer relevance. Learn how this framework helps build trustworthy AI by detecting hallucinations and ensuring responses are reliable and verifiable.