SentraNova is a federated learning platform built for healthcare. Each hospital keeps its data local — only encrypted model updates travel the network.
Each hospital trains the model on its own data. Raw patient records never leave the premises.
Each site shares privacy-preserving model updates. Patient records stay local at every institution.
All participation events are logged for compliance review and operational transparency.
The improved global model is distributed back to all participating institutions — everyone gets smarter.
Onboard your hospital or health system quickly. SentraNova connects to your existing workflows while keeping sensitive records inside your environment.
Your data stays where it is. Training happens inside your infrastructure, and only safe model updates are coordinated across the network.
Benefit from shared learning across many institutions while maintaining local control. Every participant improves over time.
Discover how training models across isolated hospital networks — without sharing patient records — is unlocking diagnostic breakthroughs impossible with siloed data.
SentraNova's architecture was designed from day one around HIPAA privacy rules, FHIR R4 interoperability, and HL7 messaging standards — so your compliance team can breathe.
Federated learning enables training on diverse, distributed patient populations — reducing the systemic bias that emerges when AI is trained on data from a single institution.
SentraNova was founded on a simple belief: hospitals should be able to collaborate on AI without compromising the trust their patients place in them.
Our team brings together expertise from healthcare informatics, cryptography, distributed systems, and regulatory compliance — building the infrastructure layer that makes federated learning practical at scale.
See SentraNova running live across simulated hospital nodes in a 15-minute demo.