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Synthetic medical data. High fidelity. Zero hassle.

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🧠 Images generated
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From idea to validation — no hospitals, no PHI, no delays.

Faster R&D Cycles

Generate datasets on demand — no waiting for hospital timelines.

Ready-to-Use Synthetic Data

No patient recruitment. No clinical delays. Deploy instantly.

Access Rare & Edge Cases

Create rare cases you can't easily collect in real-world settings.

Instant Dataset Diversity

Balance demographics without oversampling or bias.

Train Without Privacy Risk

No PHI. No legal overhead. Just clean, usable synthetic data.

Built for Model Validation

Stress-test models. Validate faster. Improve generalizability early.

Generate. Validate. Repeat.
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Built by scientists from
McGill Harvard Stanford Johns Hopkins
Backed by
ERA NYC Creative Destruction Lab Google for Startups
Used by AI teams training on...
Brain MRI – Tumors Chest CT – Nodules Spine MRI – Implants X-ray – Tubes Abdomen CT – Contrast phase

> Generate high-fidelity medical images — instantly

Simulate rare edge cases. Validate your models in minutes

// FAQs — For the Curious, Skeptical, or Just Speedrunning

Can I actually *train* on synthetic data? +
Yes. Our datasets are built for real-world model development — not academic toy problems. Teams use them for training, validation, and stress-testing pipelines.
Is this Midjourney for medical imaging? +
Pretty much. But instead of generating art, we generate structured, labeled, medical-grade datasets. No prompt engineering needed.
What’s the point if I already have data? +
Even if you have real data, it's rarely diverse enough. We help you simulate rare edge cases, balance cohorts, and de-risk model performance in the wild.
Will this hold up in a regulatory study? +
We’re working with hospitals and imaging labs to make sure it does. Our goal is FDA-compliant pipelines — not marketing hype.
Who’s this built for? +
Life sciences AI teams. Imaging companies. R&D orgs that need 10x faster dataset iteration without waiting on IRBs or patient pipelines.