AIPay managed service
Launch governed enterprise AI with less operational overhead
AIPay operates the underlying environment and upgrades while enterprise administrators control users, policies, and business usage.
Global models
Local models
Fast launch still requires explicit control boundaries
Limited internal capacity
The enterprise wants to pilot quickly without a dedicated operations team.
Fragmented maintenance
Model connections, runtime services, and platform versions require ongoing maintenance.
Governance must remain
Managed operations should not replace enterprise governance over users, policy, budgets, and reporting.
AIPay operates the service; the enterprise governs usage
Tenant isolation, retention, backup, and service targets are specified in the implementation plan and contract.
Service operations
Baseline monitoring, routine maintenance, and version upgrades.
Administrator control
Enterprise administrators configure users, permissions, budgets, and usage policy.
Periodic reporting
Provide agreed usage, cost, and operating reports.
Support service
Handle issues, changes, and incidents according to the service level.
Typical deliverables
- Managed architecture and responsibility matrix
- Tenant and administrator setup
- Launch and data policy
- Service and reporting terms
Who this is for
- Growing enterprises that need a faster launch
- Organizations without a dedicated AI platform team
- Enterprises outsourcing operations while retaining governance
Next step