Artificial Intelligence (AI) and Machine Learning (ML) Model Developers
Type of Data
Any Health Data – X-ray Images, EKGs, EHRs, etc.
Summary of Pain Point
AI and ML require sourcing diverse data, which is not always available.
Privacy regulations keep diverse data siloed in place.
Current approaches like federated learning for remotely training AI algorithms on distributed data require the entire model to be shipped to each data owner, exposing IP.
Summary of TripleBlind’s Solution
Using Blind Learning, ”Objects” can be shared with multiple counter-parties in one integration (technical and contractual).
Counter-parties never receive PII – no PII is exposed. With privacy enhancing computation, no manual de-identification is needed.
Each interaction enforces the appropriate privacy regulation (GDPR, CCPA, HIPAA, Data Residency, etc.)
Data owners keep their data in place, while the model owner never ships the full model to anyone and receives a fully trained AI model.
Similar use cases
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TripleBlind’s innovations build on well understood principles of data protection. Our innovations radically improve the practical use of privacy preserving technologies, by adding true scalability and faster processing, with support for all data and algorithm types. We support all cloud platforms and unlock the intellectual property value of data, while preserving privacy and enforcing compliance with HIPAA and GDPR.