Agent Management
Build and share cloud agents across OpenAI, Anthropic, and Copilot Studio. First Recon connects company knowledge, scoped tools, and policies in one orchestration layer.
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Create, share and oversee agents
Create and configure
Build agents on the models and company knowledge your organization has approved. Tool access runs through scoped grants, so an agent's call executes only within the permission it was given.
Share across the organization
Publish an agent for a team or the whole organization, and discover the ones colleagues already run. Policy travels with the agent. Whoever runs it, the same rules and the same record apply.
Oversee every action
Every tool call and handoff is observed inline: which agent, acting for whom, on what data, toward which destination. Actions your policy marks as high-stakes hold for human review before they execute.
Policy travels with every action
An agent action is an AI interaction like any other. Agent Management is built on AI Security Runtime, so every action an agent takes crosses the same four functions before it executes.
- 1Observe
Agent-to-tool calls and agent-to-agent handoffs on the record, with identity and destination attached
- 2Detect
Agent behavior judged by meaning and intent, drawing on the Security Context Graph, so threat and sensitive-data detection grows more accurate as your organization uses AI and connects its data
- 3Enforce
Allow, block, or hold for human review, applied to the action itself before it executes
- 4Trace
Every agent decision recorded as audit-ready evidence and streamed to your SIEM
Your questions, answered
What counts as an agent action?
Any operation an agent attempts on the governed path: a model call, a tool call such as reading a record, writing a file, or calling an API, or a handoff to another agent. The runtime treats each action as an AI interaction in its own right, with identity and policy attached before it proceeds.
What happens when an action is held?
Your policy marks which actions require a person. When an agent reaches one, the run pauses before execution. A reviewer sees the action, its context, and the policy that flagged it, then approves or denies it. Nothing executes while it waits, and when a held action is released, the record names who released it.
What does an agent leave behind?
Every action records the acting identity, attempted operation, policy, and decision. Decision metadata can be streamed to your SIEM. Held actions are visible to designated reviewers until decided; the retained trail records who approved or denied them.
Secure every AI interaction
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- Observe
- Detect
- Enforce
- Trace