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Project context

Sovereign AI Infrastructure

Private AI platform for a global maritime engineering company. Open-source models running on-premise with Kubernetes - zero data leaves the building.

Live productionGlobal maritime engineering company2025

Client identity kept confidential

Dense weave of blue network cables tracing into a switch — sovereign infrastructure
100%
Data Residency Compliance
Zero external API calls - all inference runs on-premise
Measured
6 weken
Platform Deployment
From kick-off to production-ready private AI platform
Observed
~88%
Model Quality vs Cloud
Open-source model performance relative to frontier models on domain tasks
Measured
0
External Dependencies
Fully air-gapped - no cloud AI services required
Observed

Evidence

Measured and observed during deployment inside the client infrastructure. Model quality compares a client-specific domain benchmark with selected cloud models.

The challenge

The solution

Technology stack

KubernetesLlama 3 / MistralQdrantLangChainPII RedactionPython

The result

Fully operational private AI platform running inside client infrastructure with zero external data transfer.

Engineering teams using RAG-based document search across technical manuals and project archives.

PII redaction pipeline processing documents before they enter the AI layer - compliance team signed off on day one.

Client DevOps team trained on platform operations and already extending with new use cases.

Predictable monthly infrastructure cost replacing unpredictable per-token API spend.

Next step

Want to explore where this could land first in your operation?

Start with one concrete process. In the AI Opportunity Scan we assess where AI adds value and what the best first route looks like.

Sovereign AI Infrastructure Case Study | Laava