Sovereign AI for Defence & National Security
Air-gapped, classified AI for defence and intelligence workloads — no foreign cloud, no external dependencies.
Why AI matters in defence
Defence and national security represent the highest-sovereignty tier of AI deployment: fully air-gapped environments with no external API calls, no cloud telemetry, no model weights stored outside national control, and full audit trails satisfying the most stringent security classifications.
Swibit designs and delivers AI for these environments with hardware-level security, on-prem GPU clusters, and operational independence from any foreign vendor at every layer of the stack. AI capabilities span intelligence analysis, geospatial imagery, logistics optimisation, network anomaly detection, and secure communications analytics — designed to work offline, at classification level, and with human operators firmly in the decision loop.
Use cases we deliver
Air-gapped LLM deployment for classified document analysis, intelligence synthesis, and operator support — zero external calls
Geospatial computer vision: satellite and UAV imagery analysis, change detection, and object recognition on sovereign GPU infrastructure
Secure logistics optimisation: supply chain and resource allocation AI for military and public safety operations
Network security AI: real-time anomaly detection across classified communication networks
ITSM and ITOM for classified environments: ITIL 4-aligned service management frameworks delivered on air-gapped infrastructure
Challenges we hear in this sector
Zero tolerance for external calls
No public-cloud LLM API, telemetry endpoint, or vendor phone-home is acceptable.
Classified data handling
Models, weights, training data, and outputs must all live inside classification boundaries.
Operator decision authority
AI is a force multiplier, not an autonomous actor. Operators retain decision rights.
Vendor independence
Long-term operational independence from any single foreign vendor across the stack.
Our approach
Air-gapped by design
Full stack runs offline on national hardware. No external dependency at runtime.
Open-weights, sovereign control
Open-weights models so the country retains full operational and forensic control.
Operator-centred UX
Every output is reviewable, dismissible, and traceable to a source.
Hardware-to-application sovereignty
Compute, network, models, and applications all owned and operated nationally.
What the stack looks like
- Air-gapped GPU cluster with hardware root of trust
- Classified vector store and document index
- Geospatial CV pipeline for satellite and UAV imagery
- Secure logistics and optimisation services
- End-to-end audit trail with multi-level access control
What you get
Air-gapped AI platform reference architecture and build
Two classified-domain use cases delivered end-to-end
Operator training, doctrine, and red-team exercises
Long-term operational independence runbook
Sovereign model lifecycle and forensic-grade audit tooling
A typical engagement
- 1
Scope
ClassifiedThreat modelling, classification scoping, and operator workflow analysis under NDA.
- 2
Build
Mission-definedAir-gapped stack stood up to the required classification, with formal acceptance testing.
- 3
Operate
OngoingContinuous operations with national personnel, supported by Swibit on a sovereign basis.
Regulatory posture
Questions we get asked
Can the system run completely offline?
Yes. The full lifecycle — training, fine-tuning, inference, monitoring — runs air-gapped.
Who owns the models?
You do. Weights, training data, and tooling remain under national control with documented forensic access.
How is operator authority preserved?
Every AI output is advisory, traceable to its source, and gated behind operator confirmation before any action.
Ready to build sovereign AI?
Tell us what you're working on. We respond within one business day with a clear next step.