Unknown use
Teams cannot govern AI systems they have not inventoried or assigned.
Industry context · Open
Build evidence for AI systems people can responsibly rely on
Connect data, models, human oversight, security, suppliers, and lifecycle decisions in a program people can examine and explain.
Audience and operating pressureStart with the conditions that shape the risk.
Release gaps
Models and use cases can reach production without the review their risk requires.
Provider dependence
External models, data, and infrastructure affect behavior, security, and evidence.
Operating conditions
Design for the environment the business actually operates.
Industry context changes data boundaries, supplier dependencies, decision rights, threat exposure, customer commitments, and the evidence stakeholders expect to see.
Inventory every use
Record purpose, owner, data, provider, users, affected parties, and lifecycle status.
Match review to risk
Require defined assessments and approvals before higher-impact uses advance.
Record the decision
Connect evaluations, approvals, changes, exceptions, and monitoring to owners.
Reassess on change
Trigger review when purpose, model, data, provider, behavior, or exposure changes.
Operating path
Move from operating pressure to sustained practice.
Each stage connects the material business event to ownership, execution, evidence, review, and a decision the organization can carry forward.
Inventory
Map AI systems, use cases, owners, data, providers, and affected workflows.
Assess
Review risk, controls, evidence, approval needs, and monitoring gaps.
Gate
Embed required reviews, records, approvals, and exceptions into delivery.
Monitor
Track change, performance, incidents, complaints, and required reassessment.
Evidence you can use
Show progress people can understand.
Useful evidence has a clear source, owner, timing, and review status. That makes it easier to understand, reuse, and act on.
What you receive
- A usable AI inventory
- Defined release gates
- Traceable oversight
How it stays useful
- Source
- Current source material
- Owner
- Named owner
- Timing
- Relevant period
- Status
- Review status and decision
Connected capabilities
Choose the capability that resolves the immediate pressure.
Add related work only when it improves the result. Independent review remains separate when the decision requires it.
Business results
Know what becomes possible after the work.
Each result describes a practical change the team can operate, explain, or use in its next decision.
A usable AI inventory
Systems, purposes, owners, dependencies, providers, and lifecycle status are visible.
Defined release gates
Teams know which reviews, evidence, and approvals are required before release.
Traceable oversight
Assessments, changes, monitoring, incidents, and exceptions connect to owners.
Common questions
Resolve fit, responsibility, and timing before work begins.
Straight answers on who does what, which formal path applies, and what a useful first engagement should produce.
Can you create an inventory of AI use?
Yes. We map systems, purposes, owners, data dependencies, providers, affected parties, and lifecycle status within scope.
What governance artifacts do you deliver?
A risk and review workflow, approval records, owner assignments, monitoring expectations, exception handling, and linked evidence.
Can you prepare us for ISO 42001?
Yes. We can build and test readiness for an AI management system. An accredited certification body makes any certification decision.
Will governance slow product delivery?
We place review gates where the use and risk justify them, with clear inputs and owners so teams know what is required before release.
Does Open certify an AI system as safe or lawful?
No. Open does not guarantee safety, accuracy, fairness, legality, or fitness for a specific use.
