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AI Governance

Turn AI oversight into everyday practice.

Build a practical framework for understanding, reviewing and operating your AI estate. Connect policies to the decisions people make throughout the AI lifecycle.

CONNECTED OPERATING FLOW
01Inventory & ownership
02Risk-based review
03Ongoing oversight
PRAGMA EDGEAI GovernanceContext. Ownership. Outcome.
Define the evidence, monitoring and change process needed after a use case goes live.
SERVICE CONTEXT

AI model and agent governance

Address model oversight alongside agent permissions, tool access and runtime accountability. Connect use-case inventory, evaluations and approvals with evidence from the operating workflow.

THE OPPORTUNITY

Start where it matters.

Governance gets harder when AI adoption spreads faster than visibility. A useful starting point is an inventory that connects each use case to a business owner, its data sources and the actions it may influence. Controls can then be designed around actual exposure.

CAPABILITY IN MOTION

AI Governance: from design to operation.

Governance gets harder when AI adoption spreads faster than visibility. A useful starting point is an inventory that connects each use case to a business owner, its data sources and the actions it may influence. Controls can then be designed around actual exposure.

01AI GOVERNANCE

Inventory & ownership

Establish what AI is being used, its purpose and the people accountable for it.

Put it into practice
Document use cases, models, data dependencies and lifecycle status.
AI GOVERNANCE / FROM DESIGN TO OPERATIONS

Move from AI policy to operating controls.

Governance gets harder when AI adoption spreads faster than visibility. A useful starting point is an inventory that connects each use case to a business owner, its data sources and the actions it may influence. Controls can then be designed around actual exposure.

CONNECTED OPERATING FLOW
01Make the estate visible
02Operationalize policy
03Monitor change
PRAGMA EDGEAI GovernanceContext. Ownership. Outcome.
Review changes in data, model behavior and business use with a defined escalation path.
01

Make the estate visible

Document use cases, models, data dependencies and lifecycle status.

In this stage

Establish what AI is being used, its purpose and the people accountable for it.

The handoff

A bounded use case with its owner, inputs and acceptance criteria.

02

Operationalize policy

Translate principles into approval steps, evidence and responsible owners.

In this stage

Apply review effort according to the use case, data and potential business impact.

The handoff

A working path with the required context, handoffs and review points.

03

Monitor change

Review changes in data, model behavior and business use with a defined escalation path.

In this stage

Define the evidence, monitoring and change process needed after a use case goes live.

The handoff

A reviewed operating outcome and an explicit improvement backlog.

Keep the connection going.

Connect with Pragma Edge

Start with the challenge.
Build the connection.

Bring your business goal. Let’s shape a practical next step.

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