Provides the Rhino Federated Computing Platform (FCP), a secure, scalable software solution for federated learning and collaborative data processing with no centralized data storage or transfer.
Provides the Rhino Federated Computing Platform (FCP), a secure, scalable software solution for federated learning and collaborative data processing with no centralized data storage or transfer.
Data Harmonization Engine using GenerativeAI to automatically harmonize data with human-in-the-loop validation while ensuring data stays behind the data custodians' firewalls.
Run the full data science lifecycle—exploration, data preparation, analysis, model training, validation, and inference—across distributed data environments with full control and...
Build, evaluate, and deploy AI agents on data that must stay where it lives.
What customers say
“application, which makes exploration of and collaboration with data distributed across multiple partners seamless. In this instance, we had OCT images linked to longitudinal Electronic Health Record (EHR) data and clinical notes from hundreds of patients across multiple geographies - all harmonized to the same data model via the Rhino FCP. (The hospital partners will also be able to easily reuse these assets for future research projects, lowering the barriers to collaboration.)The OutcomesOur client has also been able to take advantage of the Rhino FCP’s Secure Access (aka”
CustomerRhino Federated Computing customer
“This project and Rhino's Federated Computing capabilities enable me to take my research to the next level, as I have been able to validate and improve the generalizability of algorithms by securely leveraging diverse data from across the world, all while maximizing privacy.”
CustomerRhino Federated Computing customer
Rhino Federated Computing Platform
Children’s National Hospital used Rhino FCP to coordinate federated model training for pediatric chest X-ray classification without centralizing patient data. Rhino reports improved COVID-19 classification performance…
Assuta Medical Centers uses Rhino FCP’s Federated Datasets feature for research collaboration while keeping patient data within its infrastructure. Rhino reports that Assuta accelerated collaborations from months to…
ARC Innovation at Sheba Medical Center uses Rhino FCP’s Data Harmonization Engine to standardize clinical information across systems. Rhino’s account reports improved operational efficiency and reduced demands on…
Rhino Federated Computing Discusses Federated Learning Adoption in Clinical Trials
During a video interview at the 2026 DIA Global Annual Meeting, CEO Ittai Dayan of Rhino Federated Computing discussed the role of federated learning in overcoming data fragmentation in clinical trials. He emphasized that the technology reduces friction by enabling data analysis without centralized pooling, provided that strong incentive structures for collaboration are already in place. Dayan highlighted the Eli Lilly TuneLab program as an example where shared data leads to improved AI applications for all participants, and outlined requirements for successful enterprise-level deployment.
