AgentOps
UnclaimedMonitor, evaluate, and improve your AI agents with comprehensive observability.
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TL;DR - AgentOps
- Observability platform for AI agents with time-travel debugging
- Tracks LLM calls, token costs, and multi-agent interactions
- Free tier with 5K events/month, paid tiers available
Pricing: Free plan available
Best for: Growing teams
What is AgentOps?
AgentOps is a developer observability platform for building, debugging, and monitoring AI agents and LLM applications. It tracks events like LLM calls, tool usage, and multi-agent interactions across a wide range of models. Features include time-travel debugging to replay agent runs, complete audit trails for security and compliance, token cost tracking, and fine-tuning pipelines. Free tier covers 5,000 events/month; Pro offers paid tiers.
Available on: Web
Pros & Cons
Pros
- Time-travel debugging is genuinely unique for agent development
- Supports a wide range of models with framework-agnostic SDK
- Free tier with 5,000 events covers hobby and early-stage use
- Comprehensive audit trails meet enterprise compliance needs
- Clean dashboard with intuitive event visualization
Cons
- Paid plans may be steep for solo developers
- Enterprise features like SSO and on-prem require custom pricing
- Agent observability is a nascent category, tooling evolves fast
- Documentation could be more comprehensive for advanced use cases
Preview
Key Features
Visual event tracking for LLM calls and tool interactionsTime-travel debugging to replay agent runs step by stepComplete audit trail of logs, errors, and security threatsToken usage and cost monitoring across multiple agentsSupport for 400+ LLMs including OpenAI, Anthropic, and open-sourceFine-tuning pipelines for specialized model trainingMulti-agent interaction tracing and visualizationSDK integrations for CrewAI, Autogen, LangChain, and more
Pricing
Freemium
AgentOps offers a generous free tier with optional paid upgrades for advanced features.
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AgentOps FAQ
How does AgentOps support debugging of AI agents?
AgentOps offers time-travel debugging, allowing developers to replay agent runs to understand the sequence of events and interactions. This feature helps in identifying issues within LLM calls, tool usage, and multi-agent processes by providing a complete audit trail.
Which teams benefit most from using AgentOps?
Teams focused on developing and deploying AI agents and LLM applications will find AgentOps most beneficial. Its comprehensive observability features, including monitoring and debugging tools, are designed for developers working with complex AI systems.
How is AgentOps priced?
AgentOps is available on a free tier that covers up to 5,000 events per month. For users requiring more extensive usage and additional features, paid plans are offered, starting with a Pro plan.
Can AgentOps track token costs for LLM applications?
Yes, AgentOps includes token cost tracking as one of its features. This allows developers to monitor and manage the expenses associated with their LLM calls within their AI agents.
How does AgentOps compare to LangSmith for AI agent development?
AgentOps provides genuinely unique time-travel debugging capabilities for agent development, which allows for replaying agent runs to understand event sequences. Both platforms offer observability for AI agents, but AgentOps emphasizes this specific debugging approach and supports over 400 models.
What kind of limitations should users be aware of with AgentOps?
The Pro plan for AgentOps may be a significant investment for solo developers, and enterprise-specific features like SSO or on-premise deployment require custom pricing. Additionally, as agent observability is a rapidly evolving field, the tooling itself is subject to frequent updates and changes.
Does AgentOps integrate with a wide range of AI models?
Yes, AgentOps supports over 400 models through its framework-agnostic SDK. This broad compatibility allows developers to monitor and evaluate a diverse array of AI agents and LLM applications regardless of the underlying model.
Source: agentops.ai