Overview

Rating

10.0 / 10

Rating

Best For

Developers building multi-agent systems with frameworks like CrewAI, AG2, and the OpenAI Agents SDK who want session-level debugging

Best For

Teams building long-running AI agents, including browser and coding agents, who need to debug agent runs at scale

Product Summary

AgentOps is an open-source observability SDK for AI agents, with session replay, time-travel debugging, and cost tracking across 400+ LLMs and frameworks.

Product Summary

Laminar is an open-source observability platform for AI agents, with agent tracing, automatic failure detection, evals, and full SQL access to trace data.

Starting Price

Free Trial

Free Version

Yes

Free Version

Yes

Website

agentops.ai

Website

laminar.sh

Key features

Core capabilities each platform advertises.

AgentOps

Session replay with time-travel debugging
Decorators for sessions, agents, operations, and workflows
Multi-agent interaction graphs
Cost and token tracking across 400+ LLMs

Laminar

Agent tracing with a readable transcript view
Signals for automatic failure detection and clustering
Evals and datasets built from production traces
Full SQL access through the editor, CLI, and MCP

Strengths and tradeoffs

What each tool does well, and the limitations to keep in mind.

AgentOps

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
SSO, SLA, and SOC 2 and HIPAA coverage are Enterprise only
The free tier caps at 5,000 events

Laminar

Pros

Apache 2.0 license with Docker and Helm self-hosting
Signals surface failure modes without predefined rules
Every plan includes evals, datasets, SQL access, and the agent debugger

Cons

No prompt management, so prompt versions live in a separate tool
No LLM gateway, so routing, failover, and spend limits need another product

AgentOps or Laminar — which should you choose?

Choose AgentOps if you wantChoose if you want

Debugging multi-agent CrewAI and AG2 systems
Replaying a failed agent session step by step
Tracking LLM spend per agent session

Choose Laminar if you wantChoose if you want

Debugging long-running browser and coding agents
Finding failure patterns across thousands of agent runs
Turning recurring failures into eval datasets

Compare AgentOps and Laminar on your own traffic

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AgentOps vs Laminar (2026)

Overview

Key features

Strengths and tradeoffs

AgentOps or Laminar — which should you choose?

Compare AgentOps and Laminar on your own traffic

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