DSI designs and deploys infrastructure (cloud, on-premise or hybrid), including private AI: language models and inference running on hardware you control, sized to your workload and secured from day one.
- On-premise · Hybrid · Cloud
- Private language models
- Secured from day one
The problem
- !1
Data that cannot leave
Regulation, contracts or common sense keep your data off public AI services.
- !2
Unpredictable bills
Cloud usage that grows faster than anyone planned.
- !3
Hardware without a plan
Servers and GPUs bought, then used far below their potential.
What DSI builds
- 01
Private language models
Open models deployed and served on your own machines.
- 02
GPU sizing & setup
The right hardware for the workload, neither more nor less.
- 03
Hybrid architecture
Sensitive work local, elastic work in the cloud.
- 04
Storage & networking
Reliable data paths, backups and segmentation.
- 05
Observability
Health checks, telemetry and capacity limits from the start.
- 06
Hardening
Access control, patching and isolation built in.
How it works
- 01
Assess
Workloads, data sensitivity and existing hardware.
- 02
Size
The smallest setup that does the job well.
- 03
Deploy
Install, configure and connect.
- 04
Secure
Lock down access and isolate what's sensitive.
- 05
Operate
Monitor, update and scale.
See it work
What you get
- 01Data stays where it must
- 02Costs you can plan
- 03Models matched to your hardware
- 04Full visibility into what runs
Why it matters
Data-sovereignty requirements make on-premise AI a market of its own, and the know-how to deploy it well is scarce.
Straight talk
- Model performance depends on the hardware available. We size and benchmark together with you before committing.
Private AI & Infrastructure
Build this with DSI