Openlayer AI Agent Observability is a monitoring and tracing platform designed for agentic AI systems. It provides visibility into autonomous agent behavior by capturing detailed traces of every action, decision, API call, and tool interaction an agent makes during operation. Core capabilities include: - End-to-end tracing: Visualizes decision chains and multi-step reasoning across tools, APIs, and data sources - Real-time monitoring: Tracks performance metrics, latency, and anomalies as agents run in production - Risk and behavior analytics: Detects issues such as prompt injection attempts, bias patterns, and unintended tool usage - Custom metrics: Allows organizations to define their own metrics and thresholds aligned to internal reliability standards Primary use cases: - Production monitoring of agent responses, latency, and error rates - Incident investigation by replaying agent traces to identify where reasoning or actions went wrong - Risk detection for prompt injections, data leaks, or unauthorized tool use - Performance optimization and tuning when model or configuration changes are made The platform is built to support multi-agent environments and orchestrations, providing a unified view across interconnected agent systems. It is recognized in the 2026 Gartner Market Guide for AI Evaluation and Observability.