Evaluation and observabilityOpen sourceUpdated 2026
Phoenix
Intermediate · Observability and eval platform
Arize Phoenix is an open-source observability and evaluation tool for LLM and ML systems.
Best for
Teams debugging RAG, tracing LLM calls, and evaluating application behavior.
Why use it
Useful when you need visibility into retrieval, prompts, traces, and evals.
Tradeoffs
You still need to define useful evaluation datasets and failure categories.
Key features
- Tracing
- RAG evaluation
- Experiment analysis
Alternatives
Langfuse, Ragas, DeepEval
Where it fits
Phoenix belongs in the evaluation and observability layer of an open AI stack. Evaluate it against your model runtime, privacy needs, deployment target, and the amount of operational complexity your team can support.
CategoryEvaluation and observabilityLicenseElastic License / check repoDeploymentObservability and eval platformModeLocal/self-hosted or cloud
Phoenix GitHub →Recommendation
Use Phoenix when RAG and LLM traces need hands-on debugging.