AgentOps helps developers build, test, and deploy AI agents with confidence. The platform provides observability for OpenAI, CrewAI, Autogen, and 400+ LLMs and frameworks. You get session tracking, cost monitoring, error detection, and replay analytics to understand exactly how your agents behave. Works with minimal code integration and supports popular frameworks like Langchain, AG2, and CamelAI.

• Session Replay: Review agent execution step by step to understand decision-making processes and identify issues like recursive loops or infinite calls.
• LLM Cost Tracking: Monitor spending across 400+ LLMs and API calls with real-time visibility into token usage and costs.
• One-Line Integration: Add observability to agents, tools, and functions with minimal code overhead using decorators and SDK.
• Multi-Framework Support: Works natively with OpenAI Agents SDK, CrewAI, Langchain, Autogen, AG2, and CamelAI without custom configuration.
• Real-Time Monitoring: Track performance metrics like latency, error rates, and success codes across all agent steps and tool calls.
• User Feedback Collection: Capture explicit feedback through built-in panels and implicit signals from user behavior patterns.
• Dashboard Analytics: Visualize sessions, workflows, and performance data with comprehensive reporting and trend analysis.
• Error Detection: Quickly identify agent failures, trace root causes, and debug issues with detailed execution logs.

• Fast Setup: Initialize with a single line of code and start collecting analytics immediately without complex configuration.
• Open Source: MIT-licensed codebase allows you to explore, modify, and self-host the platform.
• Free Tier Available: Get started with 5,000 free events monthly including SDK access and replay analytics.
• Comprehensive Integrations: Native support for major agent frameworks means no custom adapters or workarounds needed.
• Cost Visibility: Real-time spending tracking prevents budget overruns and helps optimize LLM usage.
• Production-Ready Monitoring: Detect anomalies and failures in real-time to maintain agent reliability.

• Event Limits: Free tier caps at 5,000 events monthly, which may be restrictive for active development or testing.
• Limited Documentation: As a newer platform, some advanced features may lack detailed guides or examples.
• Pricing Scales Quickly: The pricing for this service scales quickly. The Pro plan starts at approximately $40 per month, and costs can increase significantly if usage exceeds the free event limit, particularly at higher volumes.

• Customer Support Automation: Monitor automated support agents that read tickets, check user history, and propose resolutions. Track response quality, resolution times, and handoff accuracy to improve customer satisfaction.
• E-commerce Chatbots: Debug product recommendation agents by reviewing query logs, product data retrievals, and final suggestions. Identify where agents fail to match user intent and optimize recommendation logic.
• Contract Review Systems: Test agents that compare legal drafts against compliance standards, flag deviations, and suggest alternatives. Ensure accuracy before deploying to production environments.
• Multi-Agent Workflows: Observe interactions between specialized agents working toward common goals. Track data exchanges, identify bottlenecks, and optimize orchestration patterns.
• Development Testing: Perform version testing between agent iterations using session replay to compare decision paths and outcomes. Identify regressions before deployment.
• Cost Optimization: Monitor LLM usage patterns across different agent implementations to identify expensive operations and optimize token consumption without sacrificing performance.