LLM evaluation tools split into testing, observability

The real story is that LLM evaluation is no longer a single tool category — it is fragmenting into offline testing, RAG-specific grading, and production observability. That is good for serious teams, but it also means buyers need to separate true eval frameworks from broader infra products with eval features.

• –Dedicated eval tools like Deepchecks, Braintrust, TruLens, and DeepEval are becoming core QA infrastructure for prompt, model, and RAG iteration
• –The roundup blurs categories by mixing benchmarking and testing products with observability platforms like Datadog and Traceloop
• –RAG-specific evaluation has clearly become its own subcategory, with grounding, retrieval relevance, and hallucination checks now table stakes
• –This is most valuable for AI engineers choosing an evaluation stack, not for readers looking for a single new launch or announcement