On-Premise Private AI / On-Prem AI & LLM
On-prem and air-gapped LLM deployment on your own hardware.
Open-weight large language models deployed on your own hardware or air-gapped environment: model selection, infrastructure design, security and access controls, for organizations where data cannot leave the building.
Frontier-hosted APIs are not an option when your data, your users, or your regulator says so. Sovereign deployment is not a different vendor. It is a different engineering practice.
- Model selection: open-weights candidates, size and quantization, evaluated against your benchmarks
- Infrastructure design: on-prem hardware sizing, private cloud, or air-gapped deployment
- Security: access controls, audit logging, prompt and output filtering, data residency controls
- Operations runbooks and a path to managed operations
Two phases. Viability study: model selection, infrastructure sizing, security posture. Two to three weeks, fixed scope. Deployment: build, integrate, harden, hand over. Timeline sized to scope.
Case studies are sector-anonymized until naming permissions are confirmed.
- What is on-prem LLM deployment?
- On-prem LLM deployment runs open-weight large language models on your own hardware, or in an air-gapped environment, so data never leaves the building. It covers model selection, infrastructure design, and the security and access controls a regulator requires.
- When is an air-gapped or private LLM required instead of a hosted API?
- When your data, your users, or your regulator will not allow information to reach a frontier-hosted API. Sovereign deployment is a different engineering practice, not a different vendor.
- How does an on-prem LLM engagement start?
- With a viability study: model selection, infrastructure sizing, and security posture, scoped over two to three weeks. Deployment then builds, integrates, hardens, and hands over, on a timeline sized to scope.
Start with the assessment.
A fixed-scope AI readiness assessment: your workflows, your data, your highest-ROI agent use cases, and a deployment roadmap. Two to four weeks.