# RAG Metrics

**RAG (Retrieval-Augmented Generation) Metrics** help you measure how well your retrieval pipelines and generation layers are performing inside **RagaAI Catalyst**. Since RAG systems combine search + LLM reasoning, monitoring both sides is critical to ensure reliability, accuracy, and efficiency.

### Why RAG Metrics matter

* **Detect gaps in retrieval**: Spot when your retriever fails to surface the most relevant passages.
* **Evaluate generated answers**: Check if the model’s outputs are grounded in retrieved context.
* **Compare retrievers and models**: Benchmark different embeddings, vector stores, or LLMs with the same dataset.
* **Optimize cost vs quality**: Find the balance between wider retrieval vs faster responses.