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 multi-modal AI agents

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

Generates synthetic multi-modal user simulations to stress-test AI agents before production, catching errors manual testing misses.

Starting Price

Free

Free Trial

Yes

Free Version

Yes

Free Version

Yes

Website

agentops.ai

Website

ashr.io

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

Ashr

Multi-modal synthetic testing
Voice/text/image simulations
Pre-production agent stress testing
Error detection
Automated test generation

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

Ashr

Pros

Addresses critical gap in systematic testing for probabilistic AI agents
Multi-modal coverage across voice, text, image, and file generation is rare
Free tier lowers adoption barrier for teams evaluating the platform
Prompt versioning with regression tracking is a strong developer experience feature
Both founders have prior AI startup experience including a successful exit

Cons

AgentOps or Ashr — 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 Ashr if you wantChoose if you want

Agent testing
Multi-modal QA
Pre-deployment validation
Edge case discovery

Compare AgentOps and Ashr on your own traffic

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AgentOps vs Ashr (2026)

Overview

Key features

Strengths and tradeoffs

AgentOps or Ashr — which should you choose?

Compare AgentOps and Ashr on your own traffic

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