Phoenix
Open-source tracing, evaluation, and iteration for AI agents
What is Phoenix?
Phoenix is an open-source platform for AI agent development and evaluation. It supports tracing, evaluation, and iteration workflows for teams building AI applications.
Its tracing tools show the steps an agent takes, including prompts, retrievals, tool calls, and outputs. This can help an engineering team investigate where an agent behavior went wrong.
Phoenix also supports evaluations that score outputs and identify issues before they reach users. Teams can build datasets from traces, run experiments, and compare results after a change.
The platform is intended for builders who want an evidence-based process for improving AI quality. It supports local, Docker, Kubernetes, and cloud deployment options according to the official product page.
Phoenix Features
Agent tracing
Phoenix shows the steps an agent takes so teams can investigate a response or failure. The trace workflow covers prompts, retrievals, tool calls, and outputs as part of an observable agent run.
Output evaluation
Phoenix helps teams build evaluations that score outputs and catch issues before release. The workflow supports testing agent quality and using results to assess whether a change improves performance.
Experiments from trace data
Phoenix supports creating datasets from traces and running experiments to test a proposed change. Teams can keep conditions consistent and benchmark performance while iterating on agents.
Pricing
Pricing not verified
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