Generate HIPAA-compliant synthetic data in hours. Backed by
ε-differential privacy with provable privacy guarantees.
Unrealized annual savings from data silos
Delay for institutional data sharing
AI projects fail due to data access issues
Every cancer model that doesn't get trained, every rare disease that stays unstudied, every clinical trial delayed 2+ years - that's the cost of our current privacy paradigm.
Deploy ML models faster with synthetic data that maintains statistical accuracy while ensuring mathematical privacy guarantees.
Share data across departments and with vendors—without exposing patient information or triggering compliance reviews.
Built for healthcare compliance from day one. HIPAA-aligned with audit-ready documentation.
Not all privacy approaches are created equal
The same differential privacy framework trusted by the world's leading organizations
Mathematically bounded privacy loss with tunable epsilon parameters
Synthetic data preserves correlations, distributions, and research utility
Complete provenance tracking for compliance and governance
Join healthcare leaders already using synthetic data
Or reach out directly: founder@synthetixdata.ai