Arize
Arize is an AI engineering platform for agent observability, evaluation, and continual learning that helps teams trace, evaluate, and improve production AI agents. It offers a managed platform (Arize AX), an open-source observability and evals tool (Phoenix), and related tooling such as the adb datastore and Alyx engineering agent.
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Quick Overview
Best for: AI Agents
What it does
AI Agents software for decision-makers comparing workflow fit and alternatives.
Best fit
AI Agents
Pricing snapshot
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Arize provides an AI engineering platform focused on tracing, evaluation, and continual learning for production AI agents. The offering includes Arize AX, a managed platform with a high-scale observability datastore and continual improvement workflows, and Phoenix, an open-source observability and evaluation tool built on OpenInference and OpenTelemetry standards. The platform targets AI engineers and teams building chatbots, RAG systems, copilots, and agent-based applications, enabling them to trace agent behavior, run large-scale evaluations, and iterate to improve agent performance and reliability.
AI observability and evaluation platform for AI applications from development to production.
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Claim this listing for $29Key Features
Observe (Tracing & Spans)
Trace what agents actually did with span, trace, and session-level observability powered by OpenInference and OpenTelemetry standards.
Evaluate (Evals Framework)
Run automated, scalable evaluations (span, trace, and session evals) to measure whether agents are improving or regressing.
Improve (Continual Learning & Testing)
Test prompts and harnesses faster and validate whether fixes improve agent performance before deploying to production, enabling a continual learning loop.
Alyx (AI Engineering Agent)
An in-app AI engineering agent that runs evals, debugs issues, and helps improve agents by suggesting fixes or running tests.
adb (Observability Datastore)
A scalable datastore for GenAI traces that stores agent trajectories and context in open formats and connects to BigQuery, Databricks, or Snowflake via DataFabric.
Phoenix (Open-source Observability & Evals)
A self-hostable, open-source tool to trace LLM calls, run evaluations, investigate failures, and keep control of data.
OpenInference Standards
Built on OpenInference semantic conventions (and OpenTelemetry) to provide interoperable, non-proprietary tracing formats for GenAI observability.
Agent-native Workflows & Integrations
Supports agent-first debugging and agent-native development across tooling such as Cursor, Claude Code, OpenCode and more.
Pricing
Current pricing details are not available from the vendor source.
Use Cases
Agent debugging and root-cause analysis
Trace agent executions and inspect spans, traces, and sessions to understand what happened inside each request and debug failures.
Automated evaluation and quality monitoring
Run scalable evals to measure agent performance over time and detect regressions or improvements in production.
Continuous improvement and prompt testing
Test prompts and harnesses, validate fixes, and close the continual learning loop to improve agent behavior before deploying changes.
Observability for generative AI applications
Support for chatbots, RAG systems, copilots, and agents to monitor production performance and improve model and workflow quality.
Integrations
OpenAI
Integrates as one of 40+ models and tools supported for tracing and evals.
Anthropic
Supported model integration for agent observability and evaluations.
Google / Amazon Bedrock
Works across cloud providers and models including Google and Amazon Bedrock.
LangGraph, LangChain, LlamaIndex
Integrates with popular agent and orchestration frameworks to capture traces and run evals.
OpenAI Agents SDK, CrewAI, DSPy
Connects to agent SDKs and tools to enable agent-native debugging and evaluation.
Benefits
Limitations
No verified limitations are available.
Frequently Asked Questions
How do I get started?
Does Arize work with my stack?
What about data privacy?
Can I use Arize for generative AI?
What’s the difference between Arize products?
Getting Started
- 1 Step 1: Connect your agent or application to Arize and send your first trace.
- 2 Step 2: Start setting up traces and run evaluations to inspect agent behavior and measure quality.
- 3 Step 3: Use Alyx (in-app agent) for guidance, or book a demo / consult docs for onboarding help.
Support
docs
Documentation and product docs (links available on the site) to set up tracing, evals, and integrations.
book a demo / sales
Book a demo from the website to get product walkthroughs and onboarding assistance.
trust center / security
Arize Trust Center provides security and compliance information and resources.
API
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