Practical applications for teams that ship, from idea to approval
Generate evidence with high quality synthetic imaging for preclinical and clinical work, accelerate endpoints, reduce screen failure, and unlock analysis that would be limited by small sample sizes
Remove data bottlenecks during model development, create balanced training sets, and test robustness across devices and vendors
Benchmark pipelines across firmware and acquisition settings, validate new features, and improve downstream AI performance
Boost internal AI projects, de risk validation, and protect privacy while collaborating across sites
Plan and evaluate population programs with safe shareable imaging that matches real world statistics
Send a small example or pick a sample pack, we will return a mini validation set and a short readout
We learn statistical structure from sources, then generate new images that do not contain patient identifiers
We benchmark against real world distributions, clinical acceptance, and downstream model performance, we also ship a validation report
MRI, CT, Ultrasound, and X ray today, more coming
Pick a sample pack or send a small example, we reply with a mini validation set and a readout within a week
