Advancing healthcare
through synthetic data

Transforming clinical research and development with privacy-preserving synthetic data generation and advanced causal inference.

Research Foundation

Advanced synthetic data generation with privacy guarantees

Our core research combines deep generative models with formal privacy frameworks to create synthetic healthcare datasets that preserve both statistical relationships and patient privacy. By integrating causal inference and differential privacy, we ensure generated data maintains clinical utility while providing mathematical privacy guarantees.

// Privacy-Preserving Generator
      G: D_real → D_syn

      // Optimization Objective
      min KL(P_real || P_syn) // Distribution matching
      s.t. privacy_loss ≤ ε // Privacy bound
      causal_structure(D_syn) ≈ // Structure preservation
      causal_structure(D_real)

Healthcare AI Platform

Production-ready synthetic data infrastructure

Our platform empowers healthcare organizations to safely generate and validate synthetic datasets at scale. Built for the complexities of healthcare data, it combines advanced privacy-preserving algorithms with automated validation pipelines to ensure both statistical fidelity and regulatory compliance. The platform seamlessly integrates with existing clinical workflows, from EHR systems to research environments.

Synthetic Generation

Generate high-fidelity synthetic datasets with configurable privacy guarantees and built-in demographic balancing

Automated Validation

Comprehensive validation suite testing statistical properties, fairness metrics, and privacy compliance in real-time

Research Integration

APIs and tools for seamless integration with clinical research pipelines, including automated documentation and audit trails

Healthcare Impact

From research to real-world applications

Healthcare organizations use our platform to unlock previously inaccessible data insights while maintaining patient privacy. Our synthetic data solutions enable rapid clinical trial design, rare disease research, and AI model development - reducing time-to-insight from months to days.

97%

Of hospital data remains unused due to privacy and access restrictions¹

12+ months

Average delay initiate health research due to data access barriers²

Faster health software development enabled by synthetic data³

1: Deloitte. A Holistic Approach to Unlock the Value of Health Data. 2023. 2: Wellcome Trust, "Delays faced by researchers trying to access data from HSCIC". 2015. 3: “DevOps and Cloud Mean the End of QA as You Know It.” CIO, 16 June 2019.

Team

Dr. Arinbjörn Kolbeinsson

Co-founder | PhD Imperial College London

A machine learning researcher with experience at Samsung AI, the University of Virginia and Evidation Health where he specialised in developing prediction models for a digital health monitoring programs that uses wearable sensor data to detect early signs of illness.

Dr. Benedikt Kolbeinsson