Why Observability for AI Agents?
Traditional APM tools weren't built for LLM-powered agents. You need purpose-built observability that understands tokens, prompts, tool calls, and the unique failure modes of autonomous systems.
Average cost reduction after implementing AgentOps analytics
Faster debugging with trace-level visibility into agent workflows
Uptime achieved with proactive performance monitoring
Key Capabilities
Token & Cost Analytics
Track token usage, API costs, and resource consumption across all your agents in real-time.
Latency Monitoring
Measure response times, identify bottlenecks, and optimize agent performance at every step.
Trace-Level Debugging
Drill into any agent interaction with full traces showing LLM calls, tool usage, and data flow.
Performance Dashboards
Visualize agent health, throughput, and error rates with customizable real-time dashboards.
User Satisfaction Metrics
Track task completion rates, user feedback, and success metrics to measure agent effectiveness.
Trend Analysis
Identify performance trends over time and get alerts before issues impact users.
Pilot Program
We're accepting a limited number of pilot customers to help shape AgentOps. Pilot participants receive hands-on support, early access to features, and influence over the product roadmap.
Apply to Become an AgentOps Pilot Customer
Share your use case and we'll reach out to discuss the pilot program.