Blueprint: Sovereign Healthcare AI Infrastructure
Reference architecture for analyzing sensitive patient records without Internet exposure, aligned with NDMO Level 4 residency requirements.
The Challenge
Healthcare authorities globally face a critical dilemma: needing to modernize patient record analysis for diagnostic accuracy while strictly adhering to data residency laws. Zero patient data can leave the national intranet.
Cloud-based solutions are often incompatible with strict data residency requirements for sensitive medical data. The challenge is to deploy "GPT-level" intelligence within a completely offline, air-gapped infrastructure.
Key Constraints
- Analyzing millions of patient records securely
- Air-gap requirement: No physical internet connection allowed
- Integration with legacy Health Information Systems (HIS)
- Critical need for Arabic medical terminology support
The Solution
The Atlas Sovereign Healthcare Blueprint deploys an Atlas Runtime Node directly within the data center. This architecture treats the AI model not as a service, but as a secure infrastructure component.
- Air-Gapped Installation: Fully offline cluster (e.g., NVIDIA H100s) running Atlas Core with zero external connectivity.
- Medical Fine-Tuning: Adapting base models using anonymized medical records to master specific Arabic medical dialects.
- RAG Pipeline: Secure integration with existing SQL/NoSQL databases using vector search without data movement.
- Operational Visibility: Infrastructure activity journal for traceability.
The Results
This architecture supports high-volume record analysis with local inference and deterministic reporting.