Basic
$0
- Includes: Up to 5,000 events, agent-agnostic SDK, LLM cost tracking across 400+ LLMs, replay analytics
AgentOps AI Review: Pricing, Open Source, Pros & Cons
Free tier, pay-as-you-go Pro, Enterprise custom
What is AgentOps?
AgentOps is an observability platform for AI agents built around the session rather than the single request. A Python SDK, with a TypeScript SDK in alpha, records LLM calls, tool calls, and multi-agent interactions, and the dashboard replays each session step by step so you can rewind to the point where an agent went wrong.
The SDK and the dashboard app are both open source under the MIT license, and the app can be self-hosted. Native integrations cover CrewAI, AG2 (formerly AutoGen), the OpenAI Agents SDK, LangChain, LlamaIndex, and others, and CrewAI ships an AgentOps option built in. Cost and token tracking run per session, with prices kept current across 400+ LLMs.
Evaluation is the thinner side of the product. The SDK supports custom eval metrics, while agent scorecards and an evaluation playground are still listed as upcoming on AgentOps' own roadmap. Prompt management and model routing aren't part of the product, so those jobs fall to other LLMOps tools.
Key features
Core capabilities this platform advertises.
- Session replay with time-travel debugging
- Decorators for sessions, agents, operations, and workflows
- Multi-agent interaction graphs
- Cost and token tracking across 400+ LLMs
Strengths and tradeoffs
What this tool does well, and the limitations to keep in mind.
Pros
- SDK and dashboard app are both MIT-licensed and self-hostable
- Session replay is organized around the full agent run, not single requests
- Native integrations with the major agent frameworks, including a built-in CrewAI option
Cons
- Evals are limited to custom metrics, with scorecards and an eval playground still on the roadmap
- No prompt management or LLM gateway
Plans & pricing
What's included in each plan, and how the tiers compare.
Pro
$40
Per month, pay as you go
- Everything in Basic, plus unlimited events, unlimited log retention, session and event export, Slack and email support, role-based permissions
Enterprise
Custom
Contact sales for a quote
Common use cases
Developers building multi-agent systems with frameworks like CrewAI, AG2, and the OpenAI Agents SDK who want session-level debugging
- Debugging multi-agent CrewAI and AG2 systems
- Replaying a failed agent session step by step
- Tracking LLM spend per agent session
Using AgentOps with Respan
Respan has a native AgentOps integration. The respan-instrumentation-agentops package takes the spans your AgentOps decorators already create and exports them through Respan, without starting AgentOps' own exporter, so you keep your instrumentation and add Respan's evals, monitors, and gateway on top.
- Keep your existing AgentOps decorators with no re-instrumentation
- Score agent sessions on live production traffic
- Alerts to Slack, email, or a webhook the moment a metric breaches
- Datasets and experiments built from real agent runs
- Prompt versions that ship without a code deploy
- One API for 1,000+ models with automatic fallbacks
Keep your AgentOps decorators and add evals with Respan
10KFree traces/mo
1,000+Models
Best AgentOps alternatives & competitors
Top companies in Observability, Prompts & Evals you can use instead of AgentOps.
Compare AgentOps
Side-by-side comparisons with other tools in this category.
Best integrations for AgentOps
Companies from adjacent layers in the AI stack that work well with AgentOps.
