AI product
Arize Phoenix is an open-source AI observability and evaluation platform developed by Arize AI for tracing, evaluating, and debugging AI agents and LLM applications. It collects traces of LLM requests and the surrounding application execution, displays them in a trace UI, and supports evaluation storage, datasets, experiments, annotations, and result comparisons. Phoenix can use OpenInference telemetry to record execution paths across multiple application steps, helping identify failures in retrieval, tool execution, or model responses; it also supports code evaluations and LLM-as-a-judge evaluations. It can run locally or be self-hosted in another environment.
3 uses taken from transcripts — each links to the moment in the video.
Open-source AI observability: trace collection, trace UI, eval storage, datasets, experiments and annotations; run locally on the laptop.
Eval library used to run tests against real data and compare candidate models
Open-source observability and evaluation platform to host and test AI agents.
3 in the library.