MLflow

Open-source LLM observability. Self-hostable, OpenTelemetry-native.

Tracing, evals, prompt management, and dataset tooling for LLM apps — self-host on your own infra or use Langfuse Cloud. The open-source default when you want full ownership of your observability stack.

LangChain's hosted observability + eval platform.

Tracing, dataset management, eval orchestration, and prompt playground from the LangChain team. Pairs naturally if LangChain or LangGraph already runs in your stack, but works standalone via SDKs.

LLM tracing + evaluation. Strong on retrieval debugging.

Phoenix is Arize's observability platform — run locally in a notebook or as a hosted service. Especially strong for inspecting RAG pipelines, finding bad chunks, and tracking retrieval quality over time.

Tracing and evaluation for LLM apps, from Weights & Biases.

An observability and evaluation toolkit for generative-AI applications. A single @weave.op decorator traces every model call — capturing inputs, outputs, latency, token cost, and errors — and the same SDK builds rigorous evaluations using LLM-as-judge and custom scorers. Traces and experiments are organized in the Weights & Biases web platform for side-by-side comparison across prompts and models.