Privacy infrastructure
for healthcare data.
We build infrastructure for provably private clinical data. Synthetic cohorts carry formal differential-privacy guarantees, so research crosses borders while patient records never do.
Every dataset
carries proof.
Each dataset synthesized on the platform receives a Clinical Privacy Index score: one number measuring statistical privacy, clinical utility, and regulatory readiness, with sub-scores per jurisdiction.
Every dataset ships with its certificate.
From raw records to
certified synthetic data.
Source data arrives as FHIR R4, HL7, CSV, or direct EHR export. The pipeline validates schema and classifies PHI fields before synthesis. No copies leave the source environment.
The privacy engine generates synthetic equivalents under formal differential-privacy guarantees, configurable to a chosen privacy–utility target. Clinical correlations and co-occurrences are preserved. Longitudinal synthesis is patent-pending.
Each output receives a Clinical Privacy Index score measuring privacy strength, clinical utility, and regulatory readiness, with sub-scores per jurisdiction.
Certified datasets export to research and ML pipelines through a standard API. Every deployment is recorded in an immutable audit trail.
Cross-border clinical intelligence corridors.
This is the grid we are building: a Stockholm-anchored network designed to connect healthcare institutions across jurisdictions. Certified synthetic cohorts move. Patient records do not.
Contact.
Write to us about your data, your constraints, and what you are trying to learn.