Observability and monitoring platform specifically designed for AI agents, providing session tracking, cost analysis, and performance optimization tools.
Dashboard and analytics specifically for AI agents — track sessions, costs, and errors so you know when your agents aren't performing well.
AgentOps is a specialized observability platform built specifically for AI agents and autonomous systems. Unlike general-purpose monitoring tools, AgentOps understands the unique patterns of agent behavior including multi-step reasoning, tool usage, and decision-making processes that span multiple LLM calls and external integrations.
The platform provides session-based tracking that groups related agent activities into cohesive workflows, making it easy to analyze complete agent interactions rather than isolated API calls. AgentOps automatically captures agent goals, planning steps, tool executions, and outcomes, providing end-to-end visibility into agent performance and behavior patterns.
AgentOps includes specialized analytics for agent-specific metrics including task completion rates, reasoning quality, tool usage efficiency, and cost attribution across different agent capabilities. The platform supports both real-time monitoring for production agents and detailed analysis for development optimization.
For debugging and optimization, AgentOps provides detailed execution traces with decision points highlighted, comparative analysis across agent versions, and identification of failure patterns. The platform integrates with popular agent frameworks including AutoGen, CrewAI, and custom implementations through simple SDK integration.
AgentOps excels in scenarios where teams need to understand and optimize complex agent behavior patterns. Development teams use it to debug multi-step agent workflows, while operations teams leverage it for monitoring autonomous systems in production environments.
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Observability and monitoring platform specifically designed for AI agents, providing session tracking, cost analysis, and performance optimization tools.
Groups related agent activities into logical sessions with goal tracking, step-by-step execution flows, and outcome analysis for complete agent interaction visibility.
Use Case:
Tracking a research agent's complete workflow from initial goal setting through information gathering, analysis, and final report generation to identify optimization opportunities.
Visual representation of complex multi-agent interactions, communication patterns, and coordination workflows with dependency mapping and bottleneck identification.
Use Case:
Visualizing how a customer service crew with researcher, analyst, and response agents collaborate to resolve complex customer inquiries and identify coordination inefficiencies.
Detailed tracking of agent tool usage patterns, success rates, performance metrics, and cost analysis with recommendations for optimization and tool selection.
Use Case:
Analyzing which tools a sales agent uses most effectively, identifying underutilized capabilities, and optimizing tool selection for different customer scenarios.
Specialized metrics for agent evaluation including task completion rates, reasoning quality scores, decision accuracy, and goal achievement tracking with trend analysis.
Use Case:
Measuring the effectiveness of different agent personalities and approaches for customer interactions, identifying which configurations produce better outcomes.
Granular cost tracking across agent activities, tool usage, and LLM calls with optimization recommendations and budget alerts for different agent workflows.
Use Case:
Understanding the cost breakdown for different agent tasks, identifying expensive operations, and optimizing agent configurations to reduce costs while maintaining quality.
Live dashboard showing active agent sessions, performance metrics, error rates, and alerts for autonomous agents running in production environments.
Use Case:
Monitoring a fleet of autonomous trading agents for anomalous behavior, performance degradation, or errors that require immediate intervention.
Free
month
$25.00/month
month
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View Pricing Options →Development teams building complex multi-agent systems requiring detailed workflow analysis
Production deployments of autonomous agents needing real-time monitoring and alerting
Cost optimization for token-intensive agent operations requiring granular usage tracking
Research teams analyzing agent behavior patterns and decision-making effectiveness
AgentOps works with these platforms and services:
We believe in transparent reviews. Here's what AgentOps doesn't handle well:
AgentOps focuses specifically on agent behavior patterns including goals, planning, multi-step reasoning, and tool usage. General LLM monitoring tracks individual model calls but doesn't understand the higher-level agent workflows and decision-making processes.
AgentOps supports both popular frameworks (AutoGen, CrewAI) through automatic instrumentation and custom agent implementations through Python SDK integration. You can track any agent system that can make API calls to log events.
AgentOps tracks agent-specific metrics including goal achievement rates, task completion times, reasoning quality scores, tool usage efficiency, cost per task, and error patterns across different agent configurations.
Yes. AgentOps provides real-time monitoring, alerting, and dashboard capabilities designed for production autonomous systems. It includes uptime monitoring, performance alerts, and error tracking specifically for agent workflows.
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