Your employees use Claude, ChatGPT, Codex, Gemini, Cursor, and agents you haven't heard of yet. Origin sits on the endpoint and gives you complete visibility into what every AI agent is doing - what it's being asked, what it's generating, and what it's doing to your systems.
Every major AI provider now ships autonomous agents that run directly on employee machines. They write code, execute commands, read and modify files, make network calls, and interact with internal systems - all at machine speed, with minimal human oversight.
Your security team has no unified way to see what these agents are doing. API-level monitoring misses agents entirely. EDR sees processes but not intent. Identity tools know who logged in but not what the agent did after. The result is an observability gap that grows with every new agent deployed.
Origin discovers and observes all of these - and every new agent that appears tomorrow - from a single endpoint sensor. No per-agent integration required.
You could monitor API gateways. You could instrument individual agent frameworks. But neither approach gives you what a system-level endpoint sensor can, because neither has access to what actually happens on the machine before the wire, during execution, and after the model's response becomes real system change.
Origin clusters agent activity into semantic topics so you can answer the question every CIO and CISO is asking: "What are our people actually doing with AI?" Instead of sorting raw logs or isolated prompts, teams can filter by agent, group, and time range to see what work is actually happening, where usage is concentrating, and which patterns stand out.
Existing controls each capture a fragment of agent behavior. The problem is that none of them preserve the semantic chain from delegated prompt to local context to system change. The endpoint does.
Origin deploys in minutes. No agent-by-agent integration. No network reconfiguration. One sensor, complete visibility.