Self-hosted AI
Data-resident and air-gapped LLM operations. Your infrastructure, our expertise.
The problem
Cloud AI services are convenient but create data residency and sovereignty problems. For some industries and some jurisdictions, the only acceptable pattern is self-hosted: the model runs on infrastructure you control, and data never leaves your network.
What we deliver
We design and deploy self-hosted LLM infrastructure on your hardware. This includes model selection (open-weight models that perform well at your scale), infrastructure sizing (GPU, memory, storage), deployment automation, and operational runbooks.
We can deploy air-gapped systems that operate with no internet connectivity. Updates and model weights are transferred via secure physical media or one-way network links.
What we handle
- Model evaluation: which open models suit your use case?
- Infrastructure sizing: what hardware do you need?
- Deployment: containerized, reproducible, version-controlled
- Monitoring: latency, throughput, error rates, model behaviour
- Operations: incident response, scaling, model updates
What this solves
You operate AI systems without dependency on external providers. Data stays on your estate. You control model weights, inference behavior, and update cadence. This is the only pattern that satisfies air-gap requirements in defense, intelligence, and critical national infrastructure.
Engagement model
Design and initial deployment: 6–10 weeks. We deliver working infrastructure, operational runbooks, and training for your team. Ongoing support available under separate SLA. We do not operate your systems for you; we build them so your team can.
Related services: Sovereign cloud integration · AI assurance