Private AI cloud
Isolated managed infrastructure for an enterprise or institution.
EXZAI Cloud
AI compute and hosting on your terms.
Evaluate dedicated, private and hybrid environments for inference, knowledge systems and AI applications, supported by clear data-handling and operational choices.
Where a model runs determines cost, latency and who can access your data. EXZAI Cloud services are being prepared to give organizations clear, documented hosting options. Each service below shows its current status.
What we deliver
Dedicated GPU instances
Reserved GPU compute for workloads requiring predictable capacity.
GPU-as-a-Service
GPU capacity rental with contractual resource profiles.
Model inference hosting
Deploy and operate supported models behind secure endpoints.
Enterprise AI API gateway
Authentication, rate limits, model routing, observability and usage controls.
Hybrid deployments
Customer premises combined with managed services or public cloud for suitable workloads.
Data residency options
The actual hosting location and data-processing arrangements are documented for each engagement.
Private retrieval pipelines
Managed embeddings, vector storage and document indexing, subject to project requirements.
Backup, resilience and disaster recovery
Designed according to the agreed service tier.
Usage analytics and optimization
Monitor compute, consumption, latency and operational costs.
Your data. Your deployment choices.
Run AI on your own servers, in a dedicated environment or in a carefully designed hybrid architecture. EXZAI helps you choose the right combination of model performance, governance, cost and operational control.
On-premises
AI on your own infrastructure
For sensitive workloads, internal network access and customer-owned hardware. Security and data residency depend on configuration and controls.
Private cloud
A dedicated, managed environment
Managed isolated infrastructure with less hardware for your team to operate. Hosting location and contractual terms are specified for each engagement.
Hybrid
Private data, selective external compute
Keep private data operations in your environment and use external compute or APIs where appropriate. Requires a data-flow map and review of cross-border considerations.
Edge & desktop
Local AI for teams and edge sites
For developer teams, local prototyping and disconnected or edge needs. Capacity depends on the chosen machine and model.
From first assessment to daily operations.
We prioritize measurable use cases, a clear technical architecture, responsible deployment and long-term maintainability.
- 01
Discover
Business outcomes, data landscape, constraints and target users.
- 02
Design
Architecture, model selection, security approach, total cost and pilot metrics.
- 03
Pilot
A narrow proof of value measured against agreed evaluation criteria.
- 04
Deploy
Production infrastructure, integrations, access, tests and documentation.
- 05
Operate
Monitoring, updates, support and optimization.
- 06
Enable
Administrator training, user adoption and ongoing improvement.
Ready to make AI work for your organization?
Tell us what you want to build. We will help define a practical technical and commercial path.