Rhino Health Platform

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We provide privacy-preserving edge computing and federated learning to facilitate data collaborations in healthcare, with robust support for the Machine Learning Operations (MLOps) workflow. Said in layman’s terms, we let AI developers work with data without ever taking possession of the data. Using the Rhino Health Platform, researchers and innovators in pharmaceuticals and medical devices can easily curate and annotate data, as well as train and deploy machine-learning models across multiple institutions, without any need for sharing data.

Rhino Federated Computing

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Rhino Federated Computing Platform (Rhino FCP) is a secure and scalable software solution designed to facilitate federated learning and collaborative data processing without the need for centralized data storage or transfer. By enabling decentralized execution with centralized control, Rhino FCP allows organizations to connect disparate data sources, process custom workloads, and scale operations while maintaining strict data privacy and security standards. Key Features and Functionality: - Decentralized Data Processing: Data remains securely behind the data custodian's firewall, eliminating the need for data transfers and ensuring compliance with privacy regulations. - AI-Enabled Data Harmonization: The AutoMapper tool leverages Generative AI to streamline data harmonization, allowing data engineers and subject matter experts to standardize data models efficiently. - Federated Learning and Inference: Supports federated statistics, learning, and inference, enabling cross-silo analytics and collaborative AI model training without compromising data sovereignty. - Granular Access Control: Implements role-based access control (RBAC) to govern data and workload access, ensuring privacy and security. - Privacy-Enhancing Techniques: Utilizes differential privacy, k-anonymization, and homomorphic encryption to protect sensitive information during processing. - Flexible Code Deployment: Allows deployment of custom code in secure containers at the data source, providing a privacy-enforcing sandbox to prevent data leakage. - Comprehensive AI Lifecycle Management: Facilitates the management of the full AI model lifecycle, including pre-processing, training, validation, and fine-tuning, with integration capabilities for third-party tools. Primary Value and Problem Solved: Rhino FCP addresses the critical challenge of enabling collaborative data analysis and AI model development across organizations without compromising data privacy or requiring data centralization. By allowing data to remain within its original environment and bringing computation to the data, Rhino FCP empowers organizations to unlock the value of their siloed data assets. This approach is particularly beneficial in regulated industries such as healthcare, life sciences, and financial services, where data privacy and compliance are paramount. By facilitating secure, efficient, and scalable collaboration, Rhino FCP accelerates innovation and enhances the development of AI-driven solutions.