tools
Arize Phoenix
Open-source platform for tracing, evaluating, and improving AI agents and LLM applications.
Arize Phoenix traces prompts, retrieval, tool calls, outputs, latency, and token usage. It supports evaluations, human annotations, datasets, experiments, prompt iteration, and OpenTelemetry-based integrations.
Developers and AI engineering teams can run it locally, in Docker, Kubernetes, notebooks, or Phoenix Cloud. Phoenix is self-hosted and open source; managed Arize AX plans and dedicated support are separate offerings.
Features
- Trace prompts, retrievals, tool calls, outputs, and agent steps
- Evaluate AI outputs with code evaluators or LLM-as-judge
- Create datasets from traces and run repeatable experiments
- Annotate traces with human feedback or automated labels
- Compare and manage prompt versions in the Prompt IDE
- Support OpenTelemetry and OpenInference tracing standards
- Run locally, in Docker, Kubernetes, notebooks, or Phoenix Cloud
- ELv2-licensed open-source core
Use cases
- Debug failed agent runs by inspecting traces and tool calls
- Evaluate retrieval quality and generated responses before release
- Create benchmark datasets from production traces
- Compare prompt or model changes through controlled experiments
- Monitor token usage, latency, errors, and AI application behavior
Pros
Cons
Pricing
- Starting price
- Free
- Pricing checked
- 2026-09-19
Self-Hosted Open Source
Free & open source
- User-managed trace spans
- User-managed ingestion volume
- User-managed projects
- User-managed retention
- Dedicated support available as an add-on