Originally published on AI Tech Connect.
What you need to know RAGAS scores RAG without answer labels. The Retrieval-Augmented Generation Assessment framework is reference-free for most of its metrics: it uses an LLM to judge retrieval and generation quality straight from the question, the retrieved context and the generated answer, so you can start measuring before you have a hand-built set of correct answers. Four core metrics, split into two halves. Faithfulness and answer relevancy judge the generation; context precision and context recall judge the retrieval. The split is the whole point — it tells you which half of the pipeline to fix. Start with faithfulness and context recall. Faithfulness catches hallucination. Context recall tells you whether your retrieval architecture is fundamentally sound. Get those two stable,…
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