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

ML engineers and AI teams, especially those in the Databricks ecosystem

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

Open-source MLOps platform with comprehensive GenAI tracing, evaluation, prompt management, and AI gateway. Maintained by the Linux Foundation.

Starting Price

Free

Free Trial

Yes

Free Version

Yes

Free Version

Yes

Website

agentops.ai

Website

mlflow.org

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

MLflow

OpenTelemetry-native tracing
50+ built-in eval metrics & LLM judges
Prompt versioning & management
Built-in AI gateway
Full MLOps lifecycle (experiments, model registry, deployment)

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

MLflow

Pros

Truly open source with Linux Foundation governance — no vendor lock-in, Apache 2.0 license
Massive ecosystem with 900+ contributors and integrations with 100+ AI frameworks across Python, TypeScript, Java, and R
Comprehensive GenAI platform with OpenTelemetry tracing, 50+ eval metrics, prompt management, and built-in AI Gateway
Unmatched adoption at 60M+ monthly downloads and 19,000+ companies globally
Unique combination of traditional MLOps and modern GenAI observability in a single platform

Cons

AgentOps or MLflow — 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 MLflow if you wantChoose if you want

LLM observability & tracing
Automated evaluation
Prompt optimization
Model deployment
Production monitoring

Compare AgentOps and MLflow on your own traffic

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AgentOps vs MLflow (2026)

Overview

Key features

Strengths and tradeoffs

AgentOps or MLflow — which should you choose?

Compare AgentOps and MLflow on your own traffic

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