Generate privacy-guaranteed synthetic healthcare datasets on-demand. Create new patient populations, extend existing cohorts, and accelerate AI development.
While competitors wait months for data access, you ship products
Differential privacy guarantees that individual patients cannot be identified, even with auxiliary information
Generate thousands of synthetic patient records in minutes, not months of approval processes
Preserves complex medical relationships, comorbidities, and demographic distributions from real data
From pharma giants to digital health startups
Projected reduction in clinical trial design time
Generate diverse patient populations for trial simulation, optimize inclusion criteria, and predict enrollment challenges before investing millions.
Potential annual savings from faster research for a large hospital
Train and validate models on unlimited synthetic data. Perfect for rare diseases where real data is scarce.
More training data available
Faster QA testing cycles
Test edge cases, develop features, and ensure HIPAA compliance without touching real patient data.
From idea to publication with synthetic data
Accelerate research timelines, enable collaboration across institutions, and publish faster with privacy-compliant datasets.
Built for healthcare's unique challenges
Our proprietary deep learning models understand complex medical relationships, ensuring synthetic data maintains clinical validity.
# Generate privacy-preserving synthetic cohort
response = k01.generate(
condition="Type 2 Diabetes",
cohort_size=10000,
demographics={"age_range": [45, 75]},
privacy_epsilon=1.0
)
Differential privacy ensures that no individual patient can be identified, even with auxiliary information.
// Privacy-preserving optimization
minimize: KL(P_real || P_synthetic)
subject to: privacy_loss β€ Ξ΅
causal_structure preserved
RESTful APIs, FHIR compatibility, and SDKs for Python, R, and JavaScript. Deploy on-premise or use our cloud.
Every synthetic dataset is automatically validated for statistical fidelity, privacy compliance, and clinical accuracy.
Start small, scale as you grow
Perfect for startups and proof of concepts
For organizations ready to scale
Supporting healthcare research & education
All plans include GDPR compliance, FHIR compatibility, and security updates.
Save 20% with annual billing.
PhDs from Imperial College London with 40+ published papers
CEO & Co-founder
ML researcher with experience at Samsung AI and Evidation Health. Specialized in predictive models for digital health monitoring using wearable sensors.
CTO & Co-founder
Computer vision specialist from Meta-acquired Scape Technologies. Expert in large-scale synthetic data generation for ML systems.
Join leading healthcare organizations using K01 to accelerate innovation