Case studies
AI teams shipping with Epineone synthetic data.
Hospitals, mobility companies and financial-services teams using synthetic datasets to train models on scenarios real data can't cover.
Healthcare imaging
Detecting rare lung pathologies with 4× less real PHI
Helix Health trained a chest X-ray classifier on a 90% synthetic corpus to catch rare pathologies their real-world data couldn't cover.
+12.4 pts AUROC on rare classesRead
Autonomous vehicles
Stress-testing perception stacks against scenarios that don't happen often enough
Northwind generated 8 million synthetic LiDAR + camera scenes covering night-time pedestrian crossings, occluded cyclists and adverse weather.
−38% critical-scenario miss rateRead
Financial services
Sharing fraud-detection benchmarks across teams without sharing real transactions
Ledger replaced a frozen, real-transaction benchmark with a differentially-private synthetic dataset that internal teams can freely iterate on.
0 PII exposed, +2.1 pts F1Read