Healthcare Technology
Clinical precision meets engineering rigor
We build software and AI systems for healthcare organizations — HIPAA-compliant systems, medical image analysis, and clinical decision support tooling. Our approach: every decision support tool is clinically validated, and every workflow is documented for the regulator before development begins.
What this covers
- HIPAA / GDPR compliance built into the architecture
- Clinical validation for every model before workflow integration
- Integration with existing PACS / EMR, not replacement
- Clear regulatory path — FDA / CE / AMAR from day one
What's inside the sector
- HIPAA / GDPR compliance built into the architecture
- Medical image analysis (radiology, pathology, derm AI)
- Clinical decision support — clinically validated models
- Integration with existing PACS / EMR / HL7 / FHIR
- Patient apps — iOS/Android compliant with healthcare standards
- Clear regulatory path — FDA / CE / AMAR from day one
- Model fairness monitoring across demographics
Who it's for
Hospital IT leadership, medtech companies, medical startups preparing a regulatory dossier.
Selected work
- Aquatis (cross-mention) — An anomaly model trained and validated under the rigor required for industrial-medical environments. The same level of rigor is required for clinical-event detection.