On-Premise AI
Open-source models on your own hardware. Your data never leaves the building.
For factories, labs, and firms with sensitive records, sending data to a third-party AI service is not an option. We run open-source models on your own servers instead — full capability, nothing sent outside.
What it is
For factories, labs, and firms with sensitive records, sending data to an outside AI service is not an option. We run open-source models on your own servers instead.
You get the capability of modern AI — retrieval, drafting, classification, agents — with none of the data leaving your network. Nothing is sent to a third party, and nothing trains someone else's model.
We work with the leading open-source families — Llama, Mistral, Qwen, DeepSeek, Gemma, and Phi — and pick the one that fits your hardware and your task.
Who it's for
- Manufacturers and labs with proprietary processes and designs to protect.
- Firms holding regulated, confidential, or client-sensitive records.
- Any operation under a policy that data cannot leave its own network.
What you get
- Open-source models deployed and running on your own hardware.
- Retrieval over your documents, kept entirely inside your network.
- The applications and agents that use those models, built to your workflow.
- Hardware right-sized to the model, so you pay for what the work needs.
- Documentation and training so your team can run it.
How we do it
In Discover we confirm the data-control requirement and the workloads that must stay inside your walls. In Design we match model to hardware and plan the deployment. In Build & deploy we stand the system up on your servers and connect it to your internal tools. In Optimize we tune it against real use and hand over a system your team can run.
It follows the same four steps we use on every engagement — see the full approach.
Proven in the field
Independent examples of this approach working in the industries we serve — construction, engineering, medical engineering, manufacturing, and renewable energy. These are cited references to others' work; they show the kind of system we build for you.
- Medical engineering
Keep sensitive records inside the building — Mayo Clinic runs imaging AI through MONAI entirely on-premise, with no patient data transmitted externally. Mayo Clinic — MONAI (opens in new tab)
- Manufacturing
Protect proprietary process data on the factory floor — NVIDIA Metropolis runs self-learning visual inspection on a local GPU at the line, so product images never leave the plant. NVIDIA — Covision Quality (opens in new tab)
- Construction
Process site data at the edge instead of the cloud — Komatsu's Smart Construction runs AI on on-site devices to turn drone scans into survey-grade data without shipping it off-site. Komatsu — Smart Construction (opens in new tab)
Questions, answered
Are open-source models good enough?
For most business tasks, yes. We match the model to the work, and grounding it in your own data matters more than raw model size.
What hardware do we need?
It depends on the model and the load. We size it with you, and many workloads run well on a single well-chosen server.
Can it connect to our internal systems?
Yes — and because it runs inside your network, it can reach systems a cloud service never could.
Who maintains it?
We hand over a documented system your team can run, or we stay on and run it for you.
Put on-premise ai to work.
Describe the workflow you'd like to fix. We'll come back within one business day with a first read on what's worth doing.