New Join early access: stress-test your medical imaging models in minutes. → Book with founders ×

Prevent AI failures before they reach patients.

Stress-test medical imaging AI. Cover blind spots with diverse patients and scanner variations. Deploy models that work in the real world.

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How it works

Upload model

Drop in your CT, MRI, or X-ray model — no PHI.

Fast setupDICOM I/O

Generate synthetic data

Create diverse cohorts with motion, low-dose, vendor mix, and labeled lesions.

MotionLow-doseVendor mix

Find failures

Surface blind spots and regressions with bias checks and AUROC/F1.

Bias checksAUROC/F1

Ship with evidence

Export regulator-ready reports and CI/CD hooks.

Reg-readyCI/CD hook

Science first. Built by researchers pushing AI in medical imaging.

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Backed by leading institutions

ERA NYC NVIDIA Inception Google for Startups Creative Destruction Lab

Build trust in every model release with Carez AI Engine

Generate cohorts → preview slices → validate bias & AUROC → ship CI/CD-ready evidence.

→ Start generating (book with founders) Browse synthetic datasets

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Carez AI — FAQs

Carez AI — FAQs

Synthetic imaging, stress testing, and building reliable AI models

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-aligned pipelines — not marketing hype.
Who’s this built for?
Life sciences AI teams. Imaging companies. R&D orgs that need 10× faster dataset iteration without waiting on IRBs or patient pipelines.
Have a question not covered here? Email the founders.