On-Premise Cloud & AI Hardware
In-house AI infrastructure with full data sovereignty
Overview
For organizations where data can't leave the building — defense, healthcare, finance, legal — we design and deploy on-premise AI infrastructure. GPU servers, private cloud, air-gapped setups, and hybrid configurations. Your models, your hardware, your control.
Capabilities
GPU Server Design
Specify and procure the right hardware — NVIDIA H100, H200, A100, L40S — for your training and inference workloads.
Private Cloud Setup
Kubernetes, VMware, or bare-metal deployments with GPU scheduling, multi-tenancy, and self-service provisioning.
Air-Gapped Deployments
Fully isolated AI environments for classified, regulated, or highly sensitive workloads.
Hybrid Architectures
Keep sensitive data on-prem while bursting to cloud for training or peak inference — best of both worlds.
Use Cases
- Classified or regulated government workloads
- Hospital systems with PHI constraints
- Financial firms with data residency rules
- Law firms protecting privileged information
- Manufacturing IP and trade secrets
- Research labs with large datasets
Ideal For
- Regulated industries (healthcare, finance, legal, defense)
- Organizations with data sovereignty requirements
- Companies with predictable high-volume inference
- Teams wanting zero cloud dependency
Frequently Asked Questions
On-prem vs cloud — which is cheaper?
At high sustained usage, on-prem wins on cost. For variable workloads, cloud is usually more economical. We model both for your specific situation.
Can we still use Claude or ChatGPT?
You can combine on-prem open-source models for sensitive workloads with cloud APIs for non-sensitive tasks. Hybrid is often the right answer.
Ready to Deploy On-Premise Cloud & AI Hardware?
Book a free AI Deep Dive and we'll map On-Premise Cloud & AI Hardware to your business needs, team capabilities, and budget.
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