Aeon AI Risk Management
Govern AI agents before they become shadow operators.
Aeon designs governance for AI systems that can use tools, hold credentials, call APIs, take actions, and escalate decisions across workflows.
Questions this page answers
- What is agentic AI governance?
- It is governance for AI systems that can use tools, hold credentials, call APIs, take actions, and escalate decisions across workflows.
- How is agentic governance different from model governance?
- Model governance focuses on model lifecycle and outputs. Agentic governance also covers tools, permissions, actions, audit trail, escalation, and human accountability.
Agents need operating controls
The risk is no longer only what a model says. It is what an agent can do, which tools it can call, and which credentials it holds.
Audit trail must be designed
Agent actions need logs that reconstruct the instruction, tool call, decision path, human checkpoint, and accountable owner.
Security and governance must meet
Aeon routes agentic AI work across implementation, CyberGuard security review, and governance evidence.