MediCore is a health-tech innovator specializing in AI-driven radiology. Their mission is to provide top-tier diagnostic tools to under-served regions globally. However, they faced significant hurdles:
- Data Privacy: Strict HIPAA/GDPR requirements made cloud processing risky.
- Connectivity: Remote clinics often suffer from poor internet bandwidth.
- Compute Power: Running heavy AI models on local clinic hardware was impossible.
We built a secure, hybrid cloud environment compliant with HIPAA and GDPR. The solution leveraged:
- Google Cloud Healthcare API: For interoperability and secure data storage.
- Kubernetes (GKE): To orchestrate model training jobs efficiently.
- Edge Computing: Deploying lightweight inference models to local devices in remote clinics with poor internet connectivity.
Diagnostic Turnaround (Hours)
Security audit and HIPAA framework setup.
Training CNN models on 18TB of anonymized data.
Optimizing models for Raspberry Pi/Edge TPU.
Deployment to 24 partner clinics.
Diagnostic turn-around time dropped from days to minutes. The platform is now used in 24 clinics, aiding in the earlier detection of critical conditions for underserved patients.
"This platform is saving lives. The ability to get MRI results in seconds instead of days changes everything for our patients in rural areas."