Agent Ops

Reviews, features, alternatives & more

AgentOps helps you build reliable AI agents with confidence. Trace every action, debug issues faster, and monitor costs in one place. Create, test, and deploy smarter AI applications with powerful insights and seamless integrations!

Back to the Directory

Improve this review

Infomation not accurate or outdated? let us know!

Last Updated On June 28, 2026

Feedback From Clint

✅ USE CASES

Building reliable AI agents becomes much easier with this powerful developer platform. It gives you complete visibility into every agent run by tracking LLM calls, tool usage, errors, and multi-agent workflows in real time. You can replay sessions, debug problems faster, monitor token usage, and keep an audit trail from development to production. It also helps control AI costs with detailed spending insights and supports more than 400 LLMs and popular agent frameworks. Whether you are testing a prototype or deploying at scale, it provides the tools needed to build, monitor, and improve AI agents with confidence.

💡 Notable Features

What sets Agent Ops apart?

🔍 Smart Agent Monitoring

Track every important event your AI agent performs in one dashboard. You can monitor LLM calls, tool usage, workflows, and agent actions as they happen. This gives you better visibility, helps identify problems quickly, and makes it easier to build reliable AI applications.

⏪ Session Replay & Time Travel Debugging

Replay complete agent sessions to see exactly what happened during every step. This feature helps you find bugs faster, understand unexpected behavior, and compare different runs without guessing. It is a huge time saver when working with complex AI agents.

💰 AI Cost & Token Tracking

Keep a close eye on token usage and API costs across multiple AI models. You can monitor spending in real time, understand where your budget goes, and optimize expensive workflows. This makes it easier to control costs as your AI projects continue to grow.

🔗 Wide Framework Integrations

Connect with over 400 LLMs and popular frameworks such as OpenAI, CrewAI, and AutoGen. The broad compatibility means you can integrate the platform into existing AI projects without rebuilding your workflow. It offers flexibility for both small experiments and enterprise systems.

📋 Complete Logs & Security Auditing

Maintain detailed records of agent activity, errors, and prompt injection attempts from development to production. These logs make troubleshooting much easier and also support security reviews and compliance needs. It gives teams greater confidence when deploying AI agents at scale.

⭐ User Reviews

What do people think about Agent Ops?

📄 Details Table

Agent Ops info, in a nutshell

Release	2023
Founder	Alex Reibman, Adam Silverman, Braelyn Boynton
Headquarters Location	San Francisco, California, USA
Popularity	Trusted by thousands of engineers
Employees	11-50 employees
Main Feature	AI agent observability with session replay, debugging, cost tracking, and monitoring.
Best For	AI Developers, Machine Learning Engineers, AI Startups etc.
Pricing	Freemium and from $40/mo
Support	Email (adam@agentops.ai)
API For Developers	Yes
Social Media

❓ Frequently Asked Questions

Agent Ops related questions, answered

🔍 What is AgentOps used for?

🛠️ Which AI frameworks does it support?

💰 Can it help reduce AI costs?

🔒 Is AgentOps safe and legit?

📊 Does it support debugging and monitoring?

🚀 Is there a free plan available?

🎁 Free Trial & Coupon

Why pay Agent Ops full price, if you can get some for free?

Free Trial Information

Free Plan	✅
Free Trial	❌

Oh no! That's a bummer :(

At this moment, Agent Ops is not offering any promotion or discount code. However, we may help you out. Subscribe to the form below and, if they will release a promo code, you will be the first one to know. 😉

👨‍🎓 Expert's Opinion

what does our expert say about Agent Ops?

From my testing, AgentOps stands out because it solves a problem many AI developers face once agents become more complex. The debugging tools, session replay, and detailed tracking make it much easier to understand what an agent is doing and why something failed. Cost tracking is another feature I found genuinely useful, especially when working with multiple LLMs. The platform also integrates with many popular frameworks, which saves setup time. The biggest drawback is that beginners may not use all of its advanced features right away. Still, for teams building serious AI agents, it offers excellent value and can speed up development significantly.