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Healthcare AI with

Learning and Edge Computing

The Rhino Health

Our platform allows developers and researchers across academia, institutions, and industry to analyze data, create AI models and deploy them - everything you would do on centralized data, but without the need to share or migrate it. This leads to faster access, reduced risk and more generalizable findings and products. This reduces the cost of development, facilitates deployment and improves outcomes across the healthcare and life sciences industry.

Rhino Health's

Our approach is grounded in edge computing and federated learning, making it possible for developers and researchers to collaborate across the healthcare ecosystem, including researchers, healthcare
organizations and industry without ever moving data, transferring ownership, or risking patient privacy.

Why do healthcare AI innovators

choose Rhino Health?

Protect Privacy

Collaborate Efficiently

Improve Outcomes

With federated learning, data remains at the site where it was created. Patient privacy is always protected. Copies of the AI model are sent to each site, and training is performed locally. You don’t need to move massive amounts of data and create redundancies. Aggregate learnings inform an optimized model. This approach to utilizing larger, more diverse datasets enables AI-based healthcare solutions to scale globally at an unprecedented pace.

do we do it?

Rhino Health strives to create equitable access to advanced AI-based diagnostics and improved treatment pathways - for all patients. This requires prioritizing patient privacy, data diversity, and trusted collaboration every step of the way in the healthcare AI lifecycle. Federated learning makes this possible.

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