Make AI trust operational and reviewable.
A central route for security, governance, data handling, evaluation, oversight and procurement. Final production claims should only describe controls that are actually implemented for the relevant service.
Security Architecture
Identity, least privilege, environment separation, encryption and secure integration principles.
Responsible AI
Risk ownership, use-case classification, human oversight and accountable deployment.
AI Inventory
Models, agents, vendors, use cases, owners and review status.
Data Protection
Purpose limitation, access, retention, minimisation and processor/subprocessor governance.
Evaluation
Quality, reliability, safety, bias where relevant, escalation and business-performance measures.
Human Oversight
Approval, escalation, exception management and material-decision controls.
Incident Management
Detection, ownership, containment, investigation and evidence.
Business Continuity
Resilience, backup, recovery and service dependencies appropriate to deployed systems.
Vendor Risk
Third-party AI/model assessment, contracts, data handling and change management.
Audit Evidence
Logs, approvals, evaluation results, policies and decision records.
Model Change Management
Versioning, re-evaluation, release gates and rollback planning.
Procurement Support
NDA, DPA, RFP, security questionnaire and vendor-onboarding routes.
Need procurement evidence?
Use the Procurement Centre for NDA, DPA, RFP, security questionnaire and vendor-onboarding enquiries.
Open Procurement Centre