Arize AI vs Opik (2026)

More than 40 integrations with models, frameworks and AI tools instrument the customer's application to send traces into Arize, code evaluators run in E2B, Daytona, Vercel or Modal sandboxes, and Data Fabric syncs trace data to warehouses. These move telemetry in and data out, and no connector lets an agent take authenticated actions in outside systems.

SourceArize, arize.com homepage and pricing and the Phoenix README on github.com/Arize-airead 2026-09-21

Integrations cover more than 40 AI frameworks, model providers and gateways, including LangChain, OpenAI, Google ADK, LangGraph and CrewAI, and alerts send webhooks out. These bring trace data in and send notifications, and none connects an agent to a business system to take actions. Through Opik Connect, Ollie reads the customer's agent codebase, writes approved fixes to it and reruns the agent from a failing trace. That is the one path that takes action, and it reaches only the local codebase.

SourceComet, comet.com/site/pricing and comet.com/docs/opik/llms.txt (Ollie, integrations)read 2026-09-21

Agents that Arize observes, evaluates and improves run elsewhere, and Arize has no workflows that sequence, branch or retry an agent's steps, or mix deterministic nodes with agent steps.

SourceArize, arize.com pricing and homepageread 2026-09-21

From traces, Opik draws the customer's agent execution graphs, the Agent Playground runs the customer's agent locally while traced, and agent configuration versions prompts, model settings and tool definitions outside the codebase. Opik runs no workflows that sequence, branch or retry steps, or that combine deterministic nodes with agent steps.

SourceComet, comet.com/docs/opik/llms.txt (development overview, agent playground) and comet.com/site/pricingread 2026-09-21

Online evals run on traces and spans as they arrive, custom monitors fire on production conditions, and Signal's agents surface failure patterns from production telemetry, trace root causes and generate proposed fixes, so Arize's work starts from incoming telemetry with no person initiating each run.

SourceArize, arize.com homepage and pricingread 2026-09-21

Online evaluation rules score production traces automatically as they are logged, Diagnostics scans a project's traces with Ollie and surfaces recurring agent issues with a root cause and suggested fix, and alerts send webhook notifications on events such as trace errors, new feedback scores and prompt changes. Evaluation and investigation start on incoming traces without a person asking.

SourceComet, comet.com/docs/opik/llms.txt (online evaluation rules, diagnostics, alerts) and comet.com/site/pricingread 2026-09-21

RAG pipelines built elsewhere are traced and evaluated in Arize, but Arize offers no retrieval structure over the customer's own documents that grounds an agent's answers.

SourceArize, arize.com homepage and pricingread 2026-09-21

RAG metrics in Opik score retrieval quality. Opik also traces the context a customer's retrieval returns and generates synthetic examples from traces for datasets. There is no document ingestion, index, retrieval layer or knowledge API that grounds an agent in company data.

SourceComet, comet.com/docs/opik/llms.txt and comet.com/site/pricingread 2026-09-21

Arize stores agent trajectories and sessions for tracing and evaluation, and there is no session, conversation or long-term memory that an agent reads back as context.

SourceArize, arize.com homepage and pricingread 2026-09-21

The customer's traces, sessions and threads are recorded, datasets and prompts are versioned, and an offline fallback replays tracing messages after an outage. There is no session, workflow or long-term memory that an agent reads and writes.

SourceComet, comet.com/docs/opik/llms.txt (tracing concepts, offline fallback) and comet.com/site/pricingread 2026-09-21

Signal generates review-ready fixes for a person to review instead of applying them, so changes Arize's agents propose pass through human review. There is no approval step, escalation rule or pause before an agent acts at run time, and no autonomy modes that treat low risk and high risk actions differently.

SourceArize, arize.com homepage and pricingread 2026-09-21

Guardrails in Opik run inline with LLM calls on live traffic and can stop or alter a response before it reaches a user, with five guard types (PII, allowed and restricted topics, prompt injection and jailbreak, an LLM-as-a-judge check, and a custom classifier) grouped into named policies that can be enforced workspace-wide, and every run logged as a span. Ollie, Opik's assistant, proposes code edits that a person reviews and approves before anything changes on disk.

SourceComet, comet.com/docs/opik/guardrails/overview and comet.com/site/pricing (Ollie, Opik Connect); comet.com/docs/opik/guardrails/overview.mdread 2026-09-21

Arize reports SOC 2 Type II, ISO 27001, PCI DSS, HIPAA and GDPR certification, with a Trust Center, and its plans include organization- and space-level RBAC, service accounts, Enterprise SSO and audit logs.

SourceArize, arize.com homepage and pricingread 2026-09-21

The Enterprise plan includes enterprise SSO over OAuth 2.0, SAML and LDAP with SSO enforcement, custom role-based access at project and organization level, view-only users, service accounts, and SOC 2, ISO 27001, ISO 9001, HIPAA and GDPR compliance. Opik also supports SAML, OIDC and JWT authentication and workspace roles and permissions, and Comet says Opik produces audit logs for governance teams.

SourceComet, comet.com/site/pricing, comet.com/docs/opik/llms.txt (authentication, roles and permissions) and comet.com/site/products/opikread 2026-09-21

Agents are traced in Arize AX on OpenTelemetry with path and graph visualizations of each agent trajectory, token, latency and cost tracking, session and multi-modal tracing, custom dashboards, metrics, monitors and views on traces, audit logs on Enterprise, retention by plan (15 days Free, 30 days Pro, custom Enterprise), and Data Fabric sync of trace data to BigQuery, Databricks or Snowflake.

SourceArize, arize.com pricing and homepageread 2026-09-21

Every step of an application's execution is traced, from context retrieval to model responses and tool calls, with agent execution graphs, sessions for multi-turn conversations, token and cost tracking and error surfacing. Traces, spans, threads, datasets and experiments export through the SDKs, REST API, UI and command line. Span retention is 60 days on Free and Pro and custom on Enterprise, and Comet says Opik produces audit logs for governance teams.

SourceComet, comet.com/site/pricing, comet.com/docs/opik/llms.txt (observability, export data) and comet.com/site/products/opikread 2026-09-21

Every Arize AX plan chooses a US, EU or CA data region, Enterprise adds self-hosted deployments, and open-source Phoenix runs locally, in containers with Docker and Helm, or in the customer's cloud.

SourceArize, arize.com pricing and the Phoenix README on github.com/Arize-airead 2026-09-21

The open source build can be downloaded, installed and run on the customer's own infrastructure from the same codebase as the hosted versions. Opik Cloud stores data in the US on the Free and Pro plans, and Enterprise offers flexible deployments across cloud, on-premises and fully managed options with a custom data region.

SourceComet, comet.com/site/pricingread 2026-09-21

Ready-made agents a customer switches on include Alyx, an AI engineering agent that runs evals, debugs issues and improves the customer's agents, and Signal, whose agents find production issues and propose fixes, each working without the other, alongside managed agents on Enterprise and packaged skills that teach coding agents to trace, evaluate and debug with Phoenix. Those are role-specific agents and ready-made workflows.

SourceArize, arize.com homepage and pricing and the Phoenix README on github.com/Arize-airead 2026-09-21

Opik ships Ollie, a ready-made assistant that reads traces, searches the workspace, builds test suites, proposes fixes and, through Opik Connect, edits and reruns the customer's agent. The same assistant powers Diagnostics, which scans traces for recurring issues. It is one packaged agent with preset uses, not a set of ready-made agents or templates a customer selects among.

SourceComet, comet.com/docs/opik/llms.txt (Ollie, diagnostics) and comet.com/site/pricingread 2026-09-21

The AI provider behind Arize's own agents and evaluators can be customized, with the customer's own key alongside Arize-managed models on Enterprise, and the Phoenix playground compares models and replays traced LLM calls against them. Customers control the models Arize's own AI features run on, though bringing their own key requires the Enterprise tier.

SourceArize, arize.com pricing and the Phoenix README on github.com/Arize-airead 2026-09-21

Through its Gateway, Opik gives a consistent API across multiple LLM providers, workspace AI Providers settings configure connections to providers, built-in LLM-as-a-judge metrics can run on a custom model, the Agent Optimizer works with OpenAI, Anthropic, Gemini, Azure and Ollama, and agent configuration keeps model settings outside the codebase, versioned and changeable without redeploying. Model choice stays with the customer, using its own providers.

SourceComet, comet.com/docs/opik/llms.txt (Gateway, AI Providers, custom model, configuring LLM providers) and comet.com/site/pricing (agent configuration)read 2026-09-21

Arize publishes Python and TypeScript client, OpenTelemetry and evals packages, a GraphQL API, a CLI that fetches traces, datasets and experiments, and a remote MCP server at each Phoenix instance's /mcp endpoint that MCP clients use to query traces, datasets and experiments, all on the OpenInference and OpenTelemetry standards it maintains. That is a stable API and SDK for Arize's own platform, with MCP served.

SourceArize, the Phoenix README on github.com/Arize-ai and arize.com homepageread 2026-09-21

There is a REST API with an OpenAPI specification and a complete Python client that work against both the open source platform and Opik Cloud, along with Python and TypeScript SDKs, native OpenTelemetry ingestion for other languages, the opik command line, and an MCP server that lets an AI coding assistant instrument code, query traces and manage prompts.

SourceComet, comet.com/docs/opik/llms.txt and comet.com/site/pricingread 2026-09-21

Testing covers online evals on traces and spans and offline evals on datasets and experiments, with trace evals of agent trajectories, session evals of multi-turn conversations, agent-as-a-judge and custom code evaluators, evaluator alignment, human annotations and labeling queues, agent experimentation in the playground, and Prompt Learning optimization. Phoenix adds open-source evals, datasets and experiments. That tests the customer's agent against datasets before production and scores quality over time.

SourceArize, arize.com pricing and the Phoenix README on github.com/Arize-airead 2026-09-21

Test suites run pass or fail assertions at item and suite level with execution policies for how many runs must pass, experiments test an application over datasets with more than 30 built-in and custom LLM-as-a-judge, heuristic and code metrics for single steps, whole agents and full conversations, annotation queues gather expert review, online evaluation scores production traces, and the Agent Optimizer tunes prompts, tools and parameters with several algorithms.

SourceComet, comet.com/site/pricing and comet.com/docs/opik/llms.txt (test suites, online evaluation, Agent Optimizer)read 2026-09-21

Arize observes, evaluates and improves agents, and its agents have no browser, desktop or computer control.

SourceArize, arize.com homepageread 2026-09-21

Opik covers tracing, evaluation, optimization, guardrails and administration, and there is no browser, desktop or computer control by an agent. The Agent Playground runs the customer's own agent locally with tracing.

SourceComet, comet.com/site/pricing and comet.com/docs/opik/llms.txtread 2026-09-21