AI GOVERNANCE
Enterprise AI governance built around approval and audit
Deploy division-specific AI agents with role-scoped access, human approval gates, traceable decisions, and a controlled path to greater autonomy.
WHO IT IS FOR
Executives, security leaders, legal teams, and operations owners evaluating how AI agents can act inside the business without bypassing accountability.
The operating problem
The governance question is not only whether an AI output is accurate. It is who can access which systems, what actions require authorization, how decisions are recorded, and how mistakes can be reversed.
What the workflow is designed to support
Scope each agent to the systems and data required for its role.
Define which actions always require human approval.
Maintain a traceable record of recommendations and decisions.
Increase permitted autonomy only after verified performance.
How implementation works
01
Assign a division and role
Start with a bounded operational purpose instead of giving one general assistant unrestricted access across the company.
02
Scope connections and permissions
Connect only the systems required for that role and define who may review or approve consequential actions.
03
Establish approval gates
Specify the emails, documents, financial actions, workflow changes, or other events that cannot proceed without authorization.
04
Review the audit trail
Use logged outcomes to evaluate performance before changing the boundaries of what the system may do.
Control remains with your team
- Division-specific and role-scoped access
- Customer-defined human approval gates
- Logged, timestamped, and reversible decisions
- Architecture designed around SOC 2 control objectives
Questions, answered
Is STIV SOC 2 certified?
STIV states that its architecture is designed around SOC 2 control objectives. Customers should request the current formal certification and audit status directly from STIV.
Can different divisions have different permissions?
Yes. The division-first model is designed so access can be scoped to the role and connected systems required for each deployment.
How does an agent earn more autonomy?
The intended model starts with review and approval. Teams can widen pre-approved activity after the recorded results support that decision.