AgentOps
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About
AgentOps is a specialized developer platform designed to bring observability and reliability to the world of AI agents and Large Language Model (LLM) applications. As a comprehensive toolset for tracing and debugging, it allows developers to move beyond black-box interactions by providing a clear window into how agents think and act. By integrating a simple SDK into their codebase, engineers can capture every event, from LLM calls and tool usage to multi-agent interactions. This visibility is crucial for identifying where an agent might be failing, hallucinating, or stuck in a loop. The platform’s core functionality revolves around visual session replays and time travel debugging, which enables users to rewind and replay specific agent runs with point-in-time precision. This is complemented by robust auditing features that track logs, errors, and even detect potential prompt injection attacks. Beyond technical performance, AgentOps provides granular financial oversight by monitoring token usage and costs across more than 400 supported LLMs. This dual focus on technical health and economic efficiency makes it a vital tool for moving agent-based projects from experimental prototypes to stable production environments. Targeted primarily at AI engineers, DevOps teams, and enterprise developers, AgentOps is particularly beneficial for those working with complex multi-agent frameworks like CrewAI and AutoGen. It serves industries where compliance and security are paramount, offering features like SOC-2, HIPAA, and NIST AI RMF adherence. For organizations looking to optimize their models, the platform also supports fine-tuning specialized LLMs based on saved completions, which can significantly reduce operational costs while improving accuracy for specific tasks. What distinguishes AgentOps from standard logging tools is its deep focus on the unique architecture of autonomous agents. Unlike generic monitoring solutions, it understands the relationship between tools, actions, and model responses in a multi-step workflow. With options for self-hosting on AWS, GCP, or Azure, and the ability to deploy on-premise, it caters to high-security enterprise needs that many cloud-only observability platforms cannot meet.
Pros & Cons
Supports over 400 different LLMs and frameworks including CrewAI and AutoGen.
Offers visual session replays for precise step-by-step debugging of agent logic.
Provides enterprise-grade compliance including SOC-2 and HIPAA for regulated industries.
Includes built-in cost tracking for real-time financial monitoring of model usage.
Enables fine-tuning of specialized LLMs at significantly reduced costs using saved data.
Basic free plan is restricted to a limit of 5,000 events.
Self-hosting and on-premise options are exclusive to the Enterprise tier.
Requires code-level integration via SDK rather than being a no-code tool.
Pro plan pricing is variable and based on a pay-as-you-go model.
Use Cases
AI engineers can use session replays to identify and fix logic errors in multi-agent workflows.
Enterprise DevOps teams can monitor production agents for prompt injection attacks and audit compliance.
Startups can track real-time LLM spend and token usage to manage operational budgets effectively.
Researchers can utilize saved completion data to fine-tune specialized models at lower costs.
Security officers can ensure AI deployments meet HIPAA and SOC-2 standards using on-premise options.
Platform
Task
Features
• fine-tuning support
• time travel debugging
• audit logging
• multi-agent interaction visualization
• prompt injection detection
• token usage counts
• llm cost monitoring
• visual event tracking
FAQs
Which LLMs and frameworks does AgentOps support?
AgentOps supports over 400 LLMs and popular agent frameworks including OpenAI, CrewAI, and AutoGen. This wide compatibility ensures developers can monitor almost any agentic workflow regardless of the underlying model.
What is 'Time Travel Debugging'?
This feature allows you to rewind and replay agent runs with point-in-time precision to see exactly what happened at each step. It helps developers isolate the specific moment an agent made an error or encountered a tool failure.
How does the cost tracking feature work?
AgentOps automatically tracks token counts and maps them to up-to-date pricing for various models to visualize your spend. It allows you to monitor total expenditure per agent or per specific research session.
Is there a way to host AgentOps on my own infrastructure?
Yes, the Enterprise plan offers self-hosting options on major cloud providers like AWS, GCP, and Azure, as well as on-premise deployment. This is ideal for organizations with strict data privacy and security requirements.
Does the platform help with security and compliance?
AgentOps provides a full data trail of logs and errors while monitoring for prompt injection attacks. For regulated industries, the platform is compliant with SOC-2, HIPAA, and the NIST AI RMF.
Pricing Plans
Pro
USD40.00 / per month• Unlimited event limit
• Unlimited log retention
• Session and event export
• Dedicated Slack support
• Dedicated email support
• Role-based permissioning
Enterprise
Unknown Price• SLA
• Slack Connect
• Custom SSO
• On-premise deployment
• Custom data retention policy
• Self-hosting (AWS, GCP, Azure)
• SOC-2, HIPAA, NIST AI RMF
Basic
Free Plan• Free up to 5,000 events
• Agent Agnostic SDK
• LLM Cost Tracking (400+ LLMs)
• Replay Analytics
Job Opportunities
There are currently no job postings for this AI tool.
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