Evaluate every layer of your RAG stack.
Retrieval quality, generation faithfulness, hallucination detection, and the framework choices that separate demoware from production RAG.
RAG quality is a stack, not a metric
Most "RAG isn't working" problems aren't model problems — they're retrieval, chunking, or context problems hidden behind a generation score. Real RAG evaluation decomposes the pipeline and measures each layer independently.
This hub maps the metrics, tools, and patterns we use to harden RAG systems for finance, healthcare, legal, and enterprise search.
Topic cluster
Deep dives, frameworks, and validation patterns across this domain.
RAGAS
Faithfulness, answer relevancy, context precision and recall — what each really measures.
Retrieval Quality
Recall@k, MRR, NDCG, and grounding-aware retrieval metrics.
Chunking Strategies
Token, semantic, hierarchical, and late-chunking trade-offs.
Embedding Evaluation
Benchmark embedding models on your own queries, not MTEB.
Hallucination Detection
Claim-level NLI, citation gating, and reference-free scoring.
Context Engineering
Reranking, deduplication, summarization, and prompt construction.
Vector Databases
Pinecone, Weaviate, Qdrant, pgvector — what to pick when.
Frequently asked
What is RAG evaluation?
Measuring retrieval quality (did we fetch the right context?) and generation quality (did the model use it faithfully?) — typically with metrics like context precision, recall, faithfulness, and answer relevancy.
What is RAGAS?
An open-source library that scores RAG systems on faithfulness, answer relevancy, context precision, and context recall using LLM-as-judge with reference-free options.
How do I detect hallucinations in RAG?
Score faithfulness against retrieved context, run claim-level NLI checks, require citations, and flag answers whose claims aren't supported by the retrieved passages.
Where do RAG systems usually break?
Bad chunking, weak embeddings, missing reranking, stale indexes, and prompts that don't constrain the model to the retrieved context.
Related hubs
Tools & comparisons
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