
Arize
AI observability and evaluation for LLMs and agents, plus open-source Phoenix.
About
Arize AI is an observability and evaluation platform for machine learning models and AI applications, founded in January 2020 in Berkeley, California by Jason Lopatecki and Aparna Dhinakaran. It started as a traditional ML monitoring tool covering drift detection and model performance dashboards, and has since expanded into LLM and AI agent observability. The company raised $131 million in total funding, including a $70 million Series C in February 2025 led by Adams Street Partners, with Datadog and PagerDuty participating.
The platform has two products. Arize AX is the commercial platform with session- and span-level tracing, LLM-as-a-judge evaluations, real-time alerts through PagerDuty and Slack, drift detection, and an AI debugging assistant called Alyx, carrying SOC 2, GDPR, and HIPAA compliance. Arize Phoenix is the open-source side built on OpenTelemetry, handling tracing, evaluation, prompt management, and experimentation, which crossed 10,000 GitHub stars in June 2026 and integrates with LangChain, LlamaIndex, the OpenAI Agents SDK, and CrewAI.
Limitation: in August 2026 Dynatrace signed a definitive agreement to acquire Arize, expected to close later that quarter subject to regulatory review. Teams standardizing on Arize should check the new owner's announcements for license, hosting, and maintenance commitments before committing long-term.
What it can do
- Session- and span-level tracing for LLM and agent workflows
- LLM-as-a-judge evaluations and drift detection
- Open-source Phoenix with prompt playground and experimentation
- Real-time alerts and AI debugging assistant (Alyx)
Setup
Sign up for Arize AX cloud or self-host Phoenix via Docker; instrument with OpenTelemetry or the OpenInference standard.
Prerequisites
An LLM application or agent pipeline to monitor; Python or TypeScript SDK for instrumentation.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 59; Trending score 85/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.