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AI infrastructure · Tool
Arize AI
ResearchedArize AI is a machine learning observability company offering Arize AX, a managed AI engineering platform, and Phoenix, an open-source observability and evals product. It helps AI teams observe, evaluate, and improve production AI agents through tracing, evaluation, experiments, and continual learning loops.
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In one minute
Start here for the decision-making essentials: what Arize AI does, who it is for, how it is accessed, and the first-party sources behind this profile.
Pricing4 options
Free signup available
AX Free tier is $0 per month
AX Pro tier is $50 per month
AX Enterprise tier is custom-priced
Platforms
Arize AX
API accessNot public
FoundedNot disclosed by source
AvailabilityWeb / remote
LicenseProprietary
Best suited to
Source-backed fit AI engineering teams building production agents Teams needing agent observability, tracing, and evaluation Developers using LLM frameworks like LangChain and LlamaIndex Organizations wanting managed or self-hosted observability Arize serves the world's most advanced AI teams. Target users include AI product managers
Decision support
6 sourced answersCommon questions and adoption checks
Short answers to the questions buyers and builders commonly ask about Arize AI. Each answer cites the shared ledger below, where every source is listed once.
01What does Arize AI help with?
Agent observability, evaluation, tracing, and experimentation · Continual learning loop for agents that turns production signals into better agents · Arize AX offers managed agents, agent experiments, expanded multimodal support, and Agent- · AI engineering platform for improving AI agents and applications by observing real behavio
Agent Observability, Evaluation & Improvement Platform | Arize AI
Ledger citation[2] arize.com
02Who is Arize AI intended for?
Arize serves the world's most advanced AI teams. · Target users include AI product managers · AI engineering teams building production agents · Teams needing agent observability, tracing, and evaluation
Arize powers leading AI teams and brands itself as powering the future of AI
Ledger citation[2] arize.com
03What pricing information is available for Arize AI?
Free signup available · AX Free tier is $0 per month · AX Pro tier is $50 per month · AX Enterprise tier is custom-priced
Free signup available
Ledger citation[4] arize.com/docs/ax
04Does Arize AI document API access?
No public API access is listed in the recorded profile sources.
The platform enables developers to monitor, debug, and continuously improve their AI agents and systems.
Ledger citation[3] arize.com/about
05What integrations does Arize AI document?
Built on OpenTelemetry and powered by OpenInference instrumentation. · Auto-instrumentation support for frameworks (LlamaIndex, LangChain, DSPy, Mastra, Vercel A · Arize AX can be set up via AI coding agents including Cursor, Claude Code, Copilot, Windsu · MCP Servers provide persistent IDE integration for instrumentation help and doc lookups · Supports Python, TypeScript/JavaScript, and Java across 30+ integrations
Built on OpenTelemetry and powered by OpenInference instrumentation.
Ledger citation[6] arize.com/docs/phoenix
06What should teams verify before adopting Arize AI?
The Single host deployment option is intended for development and testing only and is not
The Single host deployment option is intended for development and testing only and is not suitable for production use
Ledger citation[5] arize.com/docs/ax/selfhosting
Decision guide
AI infrastructureCapabilities and operating fit
This profile connects the jobs Arize AI is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
Common use cases
- Observe, Evaluate, Improve workflow for AI agents and applications
- Agent debugging through end-to-end workflows
- Continual learning loops turning production signals into better agents
- Real-time monitoring and automated alerting for production failures
- Scoring traces with LLM-based, code-based, or human evaluators
- Arize AX is designed for observing, evaluating, and improving production AI agents as part
Topics mapped
agent debuggingAgent observability, evaluation, tracing, and experimentationagent tracingAI engineering platform for improving AI agents and applications by observing real behavioAI infrastructureAlyx: AI engineering agent for every step of the workflowArize AX offers managed agents, agent experiments, expanded multimodal support, and Agent-Continual learning loop for agents that turns production signals into better agents
Verified capabilities
- Agent observability, evaluation, tracing, and experimentation
- Continual learning loop for agents that turns production signals into better agents
- Arize AX offers managed agents, agent experiments, expanded multimodal support, and Agent-
- AI engineering platform for improving AI agents and applications by observing real behavio
- Real-time monitoring and automated alerting to surface failures the moment they happen
- Alyx: AI engineering agent for every step of the workflow
- Signal: automatically surfaces issues from production traces
- Tracing captures model calls, retrieval, tool use, and custom logic step by step to debug
Recorded integrations
Built on OpenTelemetry and powered by OpenInference instrumentation.Auto-instrumentation support for frameworks (LlamaIndex, LangChain, DSPy, Mastra, Vercel AArize AX can be set up via AI coding agents including Cursor, Claude Code, Copilot, WindsuMCP Servers provide persistent IDE integration for instrumentation help and doc lookupsSupports Python, TypeScript/JavaScript, and Java across 30+ integrationsArize AX supports evaluation integrations via its Python eval library, third-party eval liArize AX integrates with LLM providers including Amazon Bedrock, Anthropic, Google GenAI, Arize AX supports agent frameworks in Python (LangChain, LangGraph, LlamaIndex, CrewAI, AuArize AX integrates with coding agents including Claude Code, Codex, GitHub Copilot, CursoThe setup pattern for tracing integrations is the same across every integration: register
Intended audiences
Access signals
- Pricing model
- Free signup available · AX Free tier is $0 per month · AX Pro tier is $50 per month · AX Enterprise tier is custom-priced
- API
- Not publicly listed
- Source links
- 34 recorded
Source-backed
Updated July 20, 2026Verified facts
Each fact points to a recorded source, making it easy to distinguish verified product information from claims that need checking.
Agent Observability, Evaluation & Improvement Platform | Arize AI
Arize AI is a machine learning observability platform · Arize offers two products: Arize AX (managed AI engineering platform) and Phoenix (open-so · Agent observability, evaluation, tracing, and experimentation
Agent observability, evaluation, tracing, and experimentation
Arize AX — a managed AI engineering platform for agents
Phoenix — an open-source observability and evals offering
Agent debugging through end-to-end workflows
Continual learning loop for agents that turns production signals into better agents
View 32 more verified facts
Arize powers leading AI teams and brands itself as powering the future of AI
Arize AX offers managed agents, agent experiments, expanded multimodal support, and Agent-as-a-Judge to help teams observe, evaluate, and improve production agents.
Arize AX is described as a Managed AI engineering platform.
Phoenix is offered as an open-source observability and evals tool.
Jason Lopatecki is Co-founder and CEO of Arize.
Aparna Dhinakaran is Co-founder and Chief Product Officer of Arize.
Arize AX is designed for observing, evaluating, and improving production AI agents as part of an automated agent improvement loop.
AI engineering platform for improving AI agents and applications by observing real behavior, evaluating quality, and proving each change works before you ship
Real-time monitoring and automated alerting to surface failures the moment they happen
Free signup available
Observe, Evaluate, Improve workflow for AI agents and applications
Alyx: AI engineering agent for every step of the workflow
Signal: automatically surfaces issues from production traces
Phoenix is built by Arize AI.
Phoenix is developed with the open-source community.
Built on OpenTelemetry and powered by OpenInference instrumentation.
Auto-instrumentation support for frameworks (LlamaIndex, LangChain, DSPy, Mastra, Vercel AI SDK), providers (OpenAI, Bedrock, Anthropic), and languages (Python, TypeScript, Java) via OpenTelemetry (OTLP).
Tracing captures model calls, retrieval, tool use, and custom logic step by step to debug behavior and understand where time is spent.
Evaluation scores traces and spans with LLM-based evaluators, code-based checks, or human labels to track performance and identify failures.
AI Observability and Evaluation Platform
Improve model performance
AI monitoring and AI Observability
Managed AI engineering platform (Arize AX)
Phoenix OSS is open-source
Open-source observability and evals (Phoenix OSS)
Arize AI is a machine learning observability platform built to unpack the proverbial AI black box.
Arize AI offers two products: Arize AX (a managed AI engineering platform) and Phoenix OSS (open-source observability and evals).
Phoenix is an open-source observability and evals product.
Arize offers cutting-edge observability and LLM evaluation for AI teams.
The platform enables developers to monitor, debug, and continuously improve their AI agents and systems.
Arize serves the world's most advanced AI teams.
Platform for building and evaluating AI agents with continuous feedback loops to improve them over time
Practical capabilities
8 documented areasWhat it helps with
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Observe, Evaluate, Improve workflow for AI agents and applications
Agent debugging through end-to-end workflows
Continual learning loops turning production signals into better agents
Real-time monitoring and automated alerting for production failures
Scoring traces with LLM-based, code-based, or human evaluators
Arize AX is designed for observing, evaluating, and improving production AI agents as part
Improve model performance
The platform enables developers to monitor, debug, and continuously improve their AI agent
Availability
Source checkedWhere it runs and where to get it
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
Cost / license
Free signup available · AX Free tier is $0 per month · AX Pro tier is $50 per month · AX Enterprise tier is custom-pricedPhoenix — an open-source observability and evals offering · Phoenix is offered as an open-source observability and evals tool. · Phoenix is developed with the open-source community.
Platforms
Arize AX — a managed AI engineering platform for agentsArize AX is described as a Managed AI engineering platform.Arize AI offers two products: Arize AX (a managed AI engineering platform) and Phoenix OSSOffers two products: Arize AX (managed AI engineering platform) and Phoenix OSS (open-sourArize AX is a managed AI engineering platformPhoenix OSS is an open-source observability and evals productAlyx is a built-in AI agent that works across the Arize AX platform, available wherever thArize AX is a managed AI engineering platform.Arize AX supports Python and TypeScript for instrumenting LLM apps.Google Cloud (GKE), Amazon Web Services, Microsoft Azure (AKS), Red Hat OpenShift, Single Arize AX
Adoption notes
DeploymentManaged AI engineering platform (Arize AX) · Arize AX is delivered as a managed platform, while Phoenix OSS is open-source (self-hosted · Arize AX supports self-hosting. · Arize AX supports self-hosted installation in the user's own environment, including on Goo
LicensePhoenix — an open-source observability and evals offering · Phoenix is offered as an open-source observability and evals tool. · Phoenix is developed with the open-source community.
Model supportNot disclosed by source
Data controlArize maintains a dedicated security program emphasizing customer trust · SOC 2 Compliant · PCI DSS Compliant · ISO/IEC 27001 Certified · GDPR Compliant
Learning curveIntermediate
Primary use casesObserve, Evaluate, Improve workflow for AI agents and applications, Agent debugging through end-to-end workflows, Continual learning loops turning production signals into better agents, Real-time monitoring and automated alerting for production failures, Scoring traces with LLM-based, code-based, or human evaluators, Arize AX is designed for observing, evaluating, and improving production AI agents as part, Improve model performance, The platform enables developers to monitor, debug, and continuously improve their AI agent, End-to-end observability for AI agents in production, Scaling LLM use cases with evaluations from day one, Online evals to boost conversions on AWS, Building state-of-the-art agents for cybersecurity, LLM Observability & Evaluation Platform, Users can start or resume a conversation, browse suggested workflows, and pick up a previo, Arize helps AI product managers iterate faster and ship trusted AI
What to verify before adopting
- The Single host deployment option is intended for development and testing only and is not
Evolution and major updates
Research in progressArize AI timeline
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
Scheduled for research
Building a reliable release history.
This profile is being checked for dated releases and material product changes. Nothing appears here until the exact date and event can be verified from a recorded source.
Dated event Short explanation Original source
Citation ledger
33 unique pagesRecorded sources
Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
- 1arize.com/trust-center 14 facts · Security
- 2arize.com 9 facts · 2 answers · Official site
- 3arize.com/about 6 facts · 1 answer · Official site
- 4arize.com/docs/ax 6 facts · 1 answer · Documentation
- 5arize.com/docs/ax/selfhosting 6 facts · 1 answer · Documentation
- 6arize.com/docs/phoenix 6 facts · 1 answer · Documentation
- 7arize.com/blog 6 facts · Official site
- 8arize.com/blog/building-ai-factory-self-improving-agents-arize-ax 6 facts · Official site
- 9arize.com/careers 6 facts · Official site
- 10arize.com/customers 6 facts · Official site
- 11arize.com/docs/ax/set-up-with-ai-assistants 6 facts · Documentation
- 12arize.com/press 6 facts · Official site
- 13arize.com/docs/ax/alyx 5 facts · Documentation
- 14arize.com/docs/ax/get-started/get-started-tracing 5 facts · Documentation
- 15arize.com/docs/ax/integrations 5 facts · Documentation
- 16arize.com/pricing 5 facts · Pricing
- 17arize.com/ai-product-manager Official site
- 18arize.com/blog-course Official site
- 19arize.com/blog-course/algorithmic-bias-examples-tools Official site
- 20arize.com/blog-course/binary-cross-entropy-log-loss Official site
- 21arize.com/blog-course/data-binning-production Official site
- 22arize.com/blog-course/drift Official site
- 23arize.com/blog/advanced-guardrails-for-llm-applications Official site
- 24arize.com/blog/ai-agents-when-and-how-to-implement-langchain-llamaindex-babyagi Official site
- 25arize.com/blog/anomaly-detection-using-large-language-models Official site
- 26arize.com/blog/applying-large-language-models-to-tabular-data Official site
- 27arize.com/blog/assessing-large-language-models Official site
- 28arize.com/blog/attention-mechanisms-in-machine-learning Official site
- 29arize.com/blog/data-quality-management-for-mlops Official site
- 30arize.com/blog/prompt-optimization-few-shot-prompting Official site
- 31arize.com/docs/ax/cookbooks Documentation
- 32arize.com/privacy-policy Security
- 33arize.com/resources/ai-product-manager-role Official site
Research status120 substantive facts · 33 source pages · quality score 91/100
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