AI governance
AI you can trust in operations.
Clear control over data, access, approvals, quality, audit evidence, and rollback — with accountable people responsible for the service.
The starting point
You are buying a service, not a model.
Accountability does not move to an algorithm.
Automation runs within agreed boundaries, produces auditable evidence, and can be narrowed or switched off while the service continues.
Operational safeguards
Eight controls, explained directly
The specific boundaries are agreed for each engagement during transition.
Who remains accountable for service outcomes?
An accountable managed service
Named RED Reply service roles remain responsible for delivery, quality, and escalation.
- Automation supports the service team; it does not replace accountability
- Every automated action has an owner who can explain and reverse it
How are identity and access controlled?
Identity and least-privilege access
Agents and automations use governed service identities with narrowly scoped permissions.
- Dedicated service identities, never shared personal accounts
- Access is reviewed and revoked through your existing processes
Which actions require human approval?
Human approval and controlled actions
Actions that change systems, records, or customer communication are explicitly governed.
- An action catalogue separates automatic, reviewed, and prohibited work
- Higher-impact changes require approval from a responsible engineer
What remains inside the customer environment?
Private integration and clear boundaries
Integration follows your data boundaries and uses private, auditable paths.
- Agreed data residency, retention, and processing boundaries per service
- No customer data used to train shared models
What is logged, observed, and auditable?
Observability, audit, and evidence
Every automated step records the request, sources, output, and resulting action.
- Model, prompt, and tool versions recorded with each run
- Evidence available for service reviews, audits, and incident reconstruction
How is answer and action quality evaluated?
Quality evaluation and continuous improvement
Quality is measured against real operational outcomes and reviewed with the service.
- Defined evaluation sets and review samples per workflow
- Quality trends discussed in regular service reviews alongside other service metrics
How are errors contained, disabled, or rolled back?
Containment, disablement, and rollback
Every automation can be narrowed, paused, or switched off while the service continues.
- Bounded scope and rate limits contain faults
- Versioned configuration restores a known-good state
How does this fit our existing governance?
Integration with your governance
AI-enabled operations run inside your existing ITSM, security, and change governance.
- Changes follow your change and release approval process
- Reporting integrates with your service management framework
Responsibility model
Who does what
Clear boundaries define customer control, RED Reply accountability, and shared decisions.
You keep
- Ownership of your data, systems, and identity provider
- Approval of the action catalogue and its boundaries
- Final say on change, release, and security governance
- The right to narrow, pause, or end any automation
RED Reply is accountable for
- Service delivery, quality, and agreed service levels
- Every automated action performed on your behalf
- Evidence, audit records, and service reporting
- Containment and rollback when something behaves unexpectedly
We do together
- Define which actions may run unattended
- Set data boundaries, retention, and access scope
- Review quality and improvement in service reviews
- Integrate reporting with your service management framework
Next step
Bring your security, risk, and governance questions.
A consolidation assessment includes the control model: what would run unattended, what stays under approval, and how evidence reaches your auditors.