Tool profile
Open-source AI observability tool for tracing, evaluations, experiments, and debugging LLM applications.
AI observability
Arize Phoenix is an open-source observability and evaluation tool for AI applications. It is built around tracing, evaluations, prompt workflows, datasets, and experiments that help teams understand how LLM systems behave and improve them with evidence instead of guesswork.
The important editorial distinction is that Phoenix and Arize AX are not the same product. Phoenix is the open-source tool; AX is Arize's paid platform. Phoenix is strongest for engineers and ML teams who want a serious open-source workflow for debugging and iteration before or alongside enterprise observability spending.
Quick fit
Editorial take
The most important editorial cleanup here is keeping Phoenix and Arize AX separate. Phoenix should be judged as an open-source observability and evaluation tool, not blurred together with the paid Arize platform.
What it does well
Primary use cases
Fit notes
Compare with
Pressure-test this pick against nearby alternatives.
Agenta
Free planLLMOps
Open-source LLMOps platform for prompt management, evaluation, observability, and collaborative AI application development with a clear hosted pricing ladder.
Choose Agenta when the team wants collaborative prompt management, evals, and observability in one hosted workflow.
Pricing snapshot
Arize offers free Phoenix and AX Free options. AX Pro starts around $50/month, AX Enterprise is custom, and overage pricing is listed separately on the official page.
AgentOps
Free planAgent observability
Observability for AI agents with tracing, debugging, session visibility, and production monitoring.
Closer to agent observability than to model hosting or prompt tooling
