Arize AX

Arize AX is a platform for tracing, evaluating and improving AI agents in production. It is best suited to teams operating complex or multi-agent systems that need investigation and experimentation in one workflow. Choose it when those controls matter more than keeping usage uncapped on an entry plan.

Overview

AX connects production telemetry with diagnosis, evaluation and iterative improvement. Signal identifies significant issues, helps uncover root causes and produces fixes ready for review. Managed Agents can investigate failed traces, repair repository bugs, automate recurring checks or be created for new tasks. This is a broader operational scope than observability alone, although teams with high incident volumes will need to watch the monthly Signal allowances.

Swarm Observability gives a real-time view of status and performance across an entire agent swarm. Agent-as-a-Judge learns from agent telemetry to create scalable evaluations aimed at exposing failures that teams did not know to test for. End-to-end experiments let teams validate agent changes and measure whether they improve performance. The combination supports a cycle from finding a failure to checking and refining the fix.

Key features

Tracing covers LLM, agent and retrieval activity, with token cost tracking and general cost tracking for teams that need to connect behavior with spend. Prompt management and LLM evaluations add controls around prompts and quality checks. Integrations include OpenAI, Anthropic, Google GenAI, Amazon Bedrock, LangChain, LangGraph, LlamaIndex, CrewAI and Vercel AI SDK, while OpenInference conventions and OpenTelemetry support standardized instrumentation.

For regulated or infrastructure-sensitive deployments, self-hosted AX keeps observability data, authentication, APIs and the user interface inside the customer environment. Air-gapped deployment is available. Arize lists SOC 2, PCI DSS, ISO/IEC 27001, GDPR and HIPAA compliance or certification in its Trust Center. SaaS plans offer US, EU or CA data regions.

Pricing

AX Free

AX Free costs nothing and includes SaaS deployment, unlimited users and evaluations, and community troubleshooting support. It allows 10 Signal issues per month, 25,000 trace spans per month, 1 GB of ingestion per month and 15-day retention. It is a sensible way to instrument a small project or assess the workflow, but the short retention and modest telemetry quotas make it unsuitable for sustained, high-volume operations.

AX Pro

AX Pro costs $50 a month, billed $50 per month. It raises the allowances to 25 Signal issues per month, 50,000 trace spans per month, 10 GB of ingestion per month and 30-day retention. Users and evaluations remain unlimited, SaaS deployment continues, and support moves to email. Pro fits a growing team that needs more history and telemetry without enterprise deployment requirements; it still requires careful capacity planning if traces or incidents grow quickly.

AX Enterprise

AX Enterprise uses custom pricing and includes unlimited Signal, custom trace-span and ingestion volumes, custom retention, unlimited users and evaluations, dedicated support, and a choice of SaaS or self-hosted deployment. It is the appropriate tier for organizations requiring tailored capacity, in-house data control or air-gapped infrastructure.

Platforms

AX is available through an API and web interface, with both SaaS and self-hosted deployment options. Free and Pro are SaaS plans; Enterprise adds self-hosting.

Who it's for

AX suits engineering and ML teams running AI agents, especially swarms, who want tracing, evaluation and experiments tied to remediation. It is also a fit for organizations that need regional SaaS hosting or customer-controlled infrastructure. Small projects can start free, while teams with strict retention, volume or isolation requirements should plan for Enterprise. It is less compelling when basic monitoring is enough or when fixed low-volume limits would interrupt normal operations.

Pros and cons

Pros

• Investigation through improvement: Signal, Managed Agents and experiments connect failure analysis with reviewed fixes and validation.
• Multi-agent visibility: Swarm Observability covers status and performance across an entire swarm rather than a single agent.
• Broad instrumentation: Major model providers and agent frameworks are supported, with OpenInference and OpenTelemetry conventions.
• Deployment flexibility: Enterprise can keep data, authentication, APIs and UI inside customer infrastructure, including air-gapped environments.

Cons

• Free-tier ceilings: Ten Signal issues, 25,000 spans, 1 GB ingestion and 15-day retention limit ongoing use.
• Pro remains capped: $50 per month buys more capacity but still limits Signal, spans, ingestion and retention.
• Enterprise pricing is custom: Budgeting requires a separate commercial discussion.

Alternatives

For an open-source framework with a free plan, consider Evidently AI; its framework is Apache 2.0 licensed and supports API, desktop and self-hosted environments.

Deepchecks is a freemium option with a Basic plan capped at three seats, one AI application, 5K DPUs per month and three months of retention.

Choose NannyML when self-managed open source or a paid Starter plan covering two models and 10 million predictions is the priority.

Opik offers open-source observability and evaluation code that can run locally.

Amazon SageMaker Autopilot is a pay-as-you-go AWS choice rather than a freemium AX-style platform.

Arthur provides freemium model monitoring with a free tier capped by use cases, projects, jobs, spans, inferences, evaluations and seven-day retention.

Fiddler AI is another freemium monitoring option with real-time guardrails and AI observability tiers.

Galileo offers a Pro plan at $100.00 per month when billed yearly, including 50,000 traces per month and advanced analytics.

For broader category comparisons, see AI Agent Observability Tools, AI LLM Observability Tools, LLM Observability Tools, Machine Learning Model Monitoring Software and Model Monitoring Software.

Verdict

Choose Arize AX if your team needs one system for agent traces, swarm monitoring, scalable evaluations and experiments that lead to fixes. Its strongest advantage is the connected improvement workflow, while its main reason to look elsewhere is the strict Free and Pro capacity limits; teams needing substantially higher volume or customer-controlled hosting should move directly to Enterprise.