AgentOps is a cutting-edge platform designed to monitor, debug, and optimize AI agents throughout their lifecycle. This comprehensive solution empowers developers to manage the entire journey of autonomous agents, from design to deployment, ensuring reliability, transparency, and scalability. With its robust features, AgentOps enables organizations to maintain high-performance AI systems while minimizing potential risks and enhancing overall agent behavior.
Features
The features of AgentOps provide a detailed suite of tools for managing AI agents effectively. From session replays to compliance checks, the platform encompasses a variety of functionalities aimed at improving the performance and reliability of AI agents. The following table summarizes the key features:
| Feature | Description |
|---|---|
| Session Replays and Analytics | Record and analyze sessions with all agent actions, LLMs, and responses in one container. |
| Event Recording | Track agent executions with detailed attributes such as ID, Session ID, and Logs. |
| Monitoring and Debugging Tools | Monitor LLM calls, costs, latency, and agent failures in real-time. |
| Recursive Thought Detection | Ensure optimal agent performance by monitoring recursive thinking patterns. |
| Time Travel Debugging | Debug and audit agent behaviors at any point in their operational timeline. |
| Comprehensive Integration | Native integrations with various frameworks to ensure compatibility. |
| Custom Reporting | Generate tailored reports to meet specific analytical needs. |
| Compliance and Security | Ensure agents operate within compliance and security standards. |
| Centralized Management | Manage various agents across processes for significant scalability. |
| Reliability | Enhance the consistency of agent behavior and minimize downtime. |
Use cases
AgentOps can be utilized in various scenarios, showcasing its versatility and effectiveness:
- Debugging Complex Agent Behaviors: Developers can leverage the time travel debugging feature to identify and rectify issues in agent behavior that may arise during their operational lifecycle.
- Performance Monitoring: Organizations can utilize real-time monitoring tools to track LLM calls and latency, ensuring that agents operate efficiently and cost-effectively.
- Compliance Auditing: The platform's security features enable businesses to ensure that their AI agents adhere to compliance standards, reducing the risk of data breaches and unauthorized access.
- Session Analysis: By using session replays, teams can analyze agent interactions to improve design and functionality based on real user data.
- Custom Reporting: Organizations can create tailored reports to gain insights into agent performance, helping to drive data-informed decision-making processes.
How to get started
To get started with AgentOps, developers can explore the platform by visiting the official website where they may find options for a trial or contact information for further inquiries. Additionally, users might be able to access a GitHub repository for implementation examples and documentation. Engaging with the support team can help clarify any questions regarding setup and integration into existing workflows.
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Pricing Plans
The following pricing plans are available for AgentOps. Please note that pricing can vary over time.
Basic Plan
Price: $0 per month (Free tier)
Features:
- Agent Agnostic SDK
- LLM Cost Tracking (for over 400 LLMs)
- Replay Analytics
Pro Plan
Price: Starting at $40 per month
Features:
- Everything in the Basic plan
- Custom Tests
- Time Travel Debugging
- Email Support
- Role-based permissioning
- LLM Threat Detection
Enterprise Plan
Price: Custom pricing
Features:
- Everything in the Pro plan
- Service Level Agreement (SLA)
- Slack Connect support
- Custom Single Sign-On (SSO)
- On-premise deployment options
- Custom data retention policy
- Self-hosting (AWS, GCP, Azure)
- Compliance certifications (SOC-2, HIPAA, NIST AI RMF)