An Agent Requests an Action
An autonomous agent initiates a proposed operation.
FROM POLICY TO ACTION
Control what agents are permitted to execute.
Governance must extend beyond what AI agents are instructed to do. It must govern what they are permitted to execute.
CONCEPTUAL GOVERNANCE WORKFLOW
An independent layer. An institutional decision.
An AI agent proposes an action. AI Agent Controller, powered by CEGS, is designed to evaluate the request against institutional policy, delegated authority, and relevant risk and approval checks.
The resulting governance decision may allow the action, block it, or escalate it for human authorization. Relevant decisions, authorizations, and action outcomes form the governance evidence.
This is a conceptual workflow, not a confirmed network proxy, inline gateway, or specific integration architecture.
AI Agent Proposes Action
AI Agent ControllerPOWERED BY CEGS
Policy evaluationAuthority verificationRisk & approval checks
Allow
Block
Escalate
Governance requirements satisfied.
Control or permission boundary violated.
Human authorization required.
Governance Evidence
Conceptual governance workflow
Four steps. A clear chain of accountability.
CEGS Evaluates the Request
Relevant authority, policy, and risk requirements are assessed.
Governance Is Enforced
The action is allowed, blocked, or escalated for human approval.
Evidence Is Preserved
Governance decisions and relevant actions are recorded for review.
Five capabilities. One governance foundation.
Monitor Agent Activity
Maintain visibility into agent activities, requested actions, and governance-relevant events.
Control Agent Authority
Define permissions, delegated authority, and the operational boundaries of autonomous agents.
Enforce Policies
Evaluate proposed actions against institutional controls before consequential actions execute.
Escalate for Human Approval
Refer sensitive actions to designated personnel, preserving human judgment and authority.
Preserve Audit Evidence
Preserve evidence of policy evaluations, approval decisions, and control outcomes.
Designed to complement existing AI environments.
The intended independent governance approach supports a common control foundation across financial operations and agent technologies, rather than requiring every agent to be rebuilt.
Deployment requirements are assessed during pilot planning. Deployment models, data access and inspection architecture, sensitive data processing and retention, exact integrations, platform compatibility, and formal security certification status remain subject to validation.
RESPONSIBLE AUTONOMY STARTS WITH CONTROL
Bring governance to the point of action.
Explore what execution-level governance could mean for your institution.