Synthetic Health Data Generation for Privacy-Preserving AI in Precision Medicine and Population Health

Findspo is a European deeptech company specializing in artificial intelligence and synthetic data generation for health, aging and population-level decision support.

We support research groups, hospitals, SMEs and consortia working in precision medicine, chronic disease management and healthy aging, particularly in contexts where access to real-world clinical or multi-omic data is limited by privacy, fragmentation, bias or low incidence rates.

Our core capability is the generation of high-fidelity synthetic health data, designed to preserve the statistical and causal properties of real datasets while eliminating re-identification risks. We work with multiple data modalities, including:

• Clinical and EHR-derived data

• Multi-omic and biomarker data

• Wearable and time-series data

• Behavioral, lifestyle and population health data

Synthetic data is used to:

• Augment small or imbalanced cohorts

• Simulate rare events and disease trajectories

• Enable cross-site and cross-country model validation

• Support federated learning and EHDS-aligned architectures

• Accelerate AI development without direct data sharing

Our approach combines GAN-based and hybrid generative models with explainable AI, ensuring that synthetic datasets are not only realistic, but also usable for clinical research, AI training and regulatory-compliant deployment.

Findspo actively collaborates in Horizon Europe, Digital Europe and health-related European consortia, contributing as a synthetic data, AI and implementation partner, with a strong focus on scalability, real-world impact and long-term sustainability.

We are open to collaborations involving:

• Precision medicine and multimodal AI

• Aging, prevention and population health

• Chronic disease and remote monitoring

• Health data spaces and privacy-preserving analytics