AI Governance Control Center

Turn fragmented AI into governable infrastructure

Policies are technically enforced, AI systems are inventoried, and relevant activities are documented for traceability.

AI Inventory

Know which AI is used across the enterprise

A central foundation for governance, internal controls and regulatory evidence.

AI system

Name, Anbieter, Version

Inventory

Purpose

Purpose and business domain

Inventory

Owner

Accountable owner

Inventory

Risk

Risk category and data types

Inventory

Status

Approval, review and lifecycle

Inventory

Region

Processing and infrastructure

Inventory
Executable Governance

Policies become technical rules

The policy engine evaluates every request consistently. Governance becomes part of execution, not just documentation.

Policy Engine · Active RulesEnforced
“HR data only through approved EU infrastructure.”Data + Region
“Marketing may use OpenAI and Claude.”Role + Model
“Contract data must not reach unapproved models.”Classification + Model
“Orders above EUR 5,000 require approval.”Action + Approval
Auditability

Traceability for every relevant AI activity

Depending on configuration, user, agent, time, model, data class, decision, approval, action and risk are recorded.

Identity Evidence

User, role, agent and tenant.

Who

Decision Evidence

Policy, routing and approval decision.

Why

Data Evidence

Data class, source and processing region.

What

Operational Evidence

Action, system access, cost and risk event.

Outcome
Start with control

Enterprise AI needs more than intelligence. It needs control.

Keep your existing models, data and systems. CODE S adds the control layer between them.

Control every modelGovern every agentProtect every interaction