Cloud Centres of Excellence for universities, research institutions, and government agencies — shared GPU platform with domain specialization and academic governance.
Problem
Universities and research labs need GPU compute, collaborative environments, and domain tooling. But procurement takes months, hardware depreciates, utilization is uneven across departments, and there is no shared governance model for multi-faculty AI infrastructure.
CCoE Framework
A shared platform that respects departmental autonomy while providing institutional governance.
Multi-faculty access with research group isolation, project-level permissions, and institutional admin oversight. Federated identity with university LDAP/SAML.
Pool GPU resources across departments with fair-share scheduling, priority queuing for deadlines, and transparent cost allocation per department/grant.
HPC workloads, large-scale training, reproducible environments, and dataset management. Publication-ready outputs with execution lineage.
Cross-university projects with federated identity, shared workspaces, and controlled data sharing. Multi-institution consortia supported.
Department-level reporting, grant-code tracking, capacity planning, and utilization optimization. Clear ROI evidence for funding bodies.
Research data handling with appropriate security levels. Sensitive data projects get isolated workspaces. Ethics board integration for AI research.
CCoE Models
Multi-department platform with faculty-level governance, student access tiers, and research project isolation.
Domain-focused platform for national labs and research organizations with publication workflow integration.
Sovereign deployment with security clearance integration, air-gapped option, and inter-agency collaboration.
Multi-institution platform with federated governance, shared datasets, and joint compute pools.
Enterprise capability centres — the corporate equivalent of institutional CCoE.
Managed HPC and burst computing for research workloads.
How universities use the platform for research and teaching.
Remote GPU labs and curriculum delivery at scale.
From intent to verified engineering artifact.