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AgentOps

Freemium#13 of 26 in LLM Observability ToolsAI Agent Observability ToolsLlm Monitoring

Trace, debug, and deploy AI agents and LLM applications.

7.7/10Editor score
AgentOps7.7 Visit AgentOps

At a glance

  • Editor score
    7.7 / 10
  • Pricing
    Free plan · paid from $40/mo
  • Best for
    Agent teams needing replay and audit visibility
  • Free plan
    Yes
  • Paid from
    $40/mo
  • LLM tracing
    Yes
  • Facts checked
    20 Sep 2026
  • Where it wins

    • Time-travel replay with event visualization and replay analytics
    • Tracks tokens and costs across more than 400 LLMs
    • Supports exports, permissions, self-hosting, and on-premise deployment
  • Where it doesn't

    • Basic includes a 5,000-event limit
    • Pro pricing is usage-based and starts at $40 per month
    • Evaluation and prompt-management workflows are not core documented features

Our verdict on AgentOps

AgentOps is a developer platform for observing, debugging, and deploying AI agents and LLM applications. Its SDK instruments LLM calls, tools, actions, errors, and multi-agent interactions, then presents sessions and event timelines in a web dashboard. It is aimed at teams that need replay and audit visibility across agent workflows, including prompt-injection tracking, retrieval tracing, token counting, and cost analysis. Deployment options cover both a hosted web platform and self-hosting.

The published plans show a useful progression. Basic costs $0 per month and includes an agent-agnostic SDK, LLM cost tracking for more than 400 LLMs, and replay analytics; the official homepage also shows a 5,000-event allowance. Pro starts at $40 per month, billed monthly, and adds an unlimited event limit, unlimited log retention, session and event export, dedicated Slack and email support, and role-based permissions. Enterprise adds SLA, Slack Connect, custom SSO, on-premise deployment, custom data-retention policies, and self-hosting on AWS, GCP, or Azure. Pro is described as pay as you go, so teams should assess expected usage alongside the starting price.

Ecosystem coverage is a strong fit for modern agent stacks. Integrations include OpenAI, Anthropic, Google Generative AI, LiteLLM, Watsonx.ai, LangChain, LangGraph, LlamaIndex, OpenAI Agents SDK, AutoGen, CrewAI, Google ADK, Mem0, AG2, Agno, and other listed frameworks. The standout capability is the combination of event timelines, time-travel replay, debugging, audit trails, and prompt-injection tracking. Choose AgentOps when traceability, replay, cost visibility, and deployment control are priorities. Teams primarily seeking built-in evaluation or prompt-management workflows should compare tools centered on those functions.

AgentOps pricing

Plans Free plan · paid from $40/moFreemium A usable free plan; paid tiers unlock the limits above. Prices re-checked Sep 2026.
See plans on agentops.ai

All 3 AgentOps plans and prices →

AgentOps fact sheet

Free planYes
Paid from$40/mo
LLM tracingYes
LLM evaluationsNot verified
Prompt managementNot verified
Agent tracingYes
Retrieval tracingYes
Token cost trackingYes
Deployment optionsBoth
DeploymentCloud, Self-hosted
PlatformsWeb
Compliance & securitySOC 2, HIPAA
SupportEmail, Docs
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations400+ integrations: OpenAI, Anthropic, Google Generative AI, LiteLLM, Watsonx.ai, Mem0 …
PricingFree plan · paid from $40/mo (source)
Websiteagentops.ai
Facts checked20 Sep 2026

AgentOps integrations

AgentOps lists 400+ integrations on its own site — the 20 named here are the ones its pages call out.

  • OpenAI
  • Anthropic
  • Google Generative AI
  • LiteLLM
  • Watsonx.ai
  • Mem0
  • AG2
  • Agno
  • AutoGen
  • CrewAI
  • Google ADK
  • LangChain
  • LangGraph
  • LlamaIndex
  • OpenAI Agents SDK
  • Smolagents
  • Haystack
  • Memori
  • xAI
  • Xpander

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Featured on iTechGuides

Featured on iTechGuides — AgentOps 7.7/10

AgentOps is listed in our LLM Observability Tools directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026

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