ATOMIC · in-house medical AI
Help build medical AI — safely.
We train our own medical AI models in-house. Approved academics and clinicians can contribute data, knowledge and corrections to make them better — through a review process that cannot degrade a model already in service.
Models in development
What we're building
Each model learns continuously and safely. Open a roadmap to see what's live, what's next, and the data that would help most.
How contributing works
From your data to a better model
You never train the model directly — you contribute into a reviewed pipeline that we run.
Get approved
Request access; we verify your academic or clinical credentials once.
Contribute
Submit de-identified data, knowledge or corrections for a specific model and aspect.
We review
Automatic screening plus human approval — nothing trains until it's cleared.
It earns its place
Approved data is used only if a new version beats a sealed test. You're credited.
Why contributions can't harm a live model
New data only ever produces a candidate version. A candidate replaces the model in service only if it does not score worse on a sealed test set that contributors never see or touch. If a contribution is wrong or low-quality, the candidate simply fails that test and is discarded — the model people rely on is never affected, and every contribution is attributed and reversible.
Ready to contribute?
Request contributor access and help move medical AI forward.