Rhino Federated Computing

Rhino Federated Computing develops the Rhino Federated Computing Platform (Rhino FCP), software for federated learning and collaborative data processing that executes code where data resides instead of centralizing it. The platform connects to existing data sources across cloud and on-premises environments, harmonizes heterogeneous data, and returns only aggregated results, so datasets remain behind each data custodian's firewall and no data transfer or centralized storage is required. Capabilities span federated statistics, federated learning and federated inference, with support for frameworks such as PyTorch, TensorFlow and scikit-learn, as well as LLMs, and federated MLOps for managing pre-processing, training, validation, fine-tuning and deployment across distributed environments.

Access is provided through a web interface and an extensible SDK/API, with role-based access control, customer-managed encryption keys, audit logs, and deployment of custom code in secure containers at the data source. Privacy-enhancing techniques include differential privacy, k-anonymization and homomorphic encryption, and the platform states adherence to ISO 27001, SOC 2 Type II, HIPAA and GDPR. A Data Harmonization Engine with a GenAI-based AutoMapper supports semantic and syntactic mapping to standards such as FHIR and OMOP with human-in-the-loop validation. More recent additions include an MCP server for natural-language querying of data and for building governed agentic AI workflows. Product documentation covers projects, collaborators, secure access lists, datasets and federated datasets, data schemas, code objects and runs, confidential computing environments, and NVFlare-based workloads.

The company organizes its offerings as Rhino Federated Intelligence and Rhino Data Activation, and describes production deployments in biopharma, oncology research, health systems and pan-European research consortia, plus financial services and public sector use cases.

Founding story

The company grew out of EXAM, a global study led by Dr. Ittai Dayan and published in Nature Medicine, which used federated learning to train and test AI models across data from 20 institutions worldwide without centralizing sensitive data. Rhino was founded in 2020 by Dayan, who previously led AI development and deployment at Mass General Brigham and was a researcher at Harvard Medical School, together with serial entrepreneur Yuval Baror, with the aim of turning federated computing into enterprise-grade software infrastructure.

Business model

Rhino licenses enterprise software infrastructure to organizations that need to run AI, analytics and data workflows on distributed, regulated data, deployed into customers' own cloud or on-premises environments rather than aggregating data in a Rhino-operated repository.

Traction

Company materials cite production deployments including the federation infrastructure behind a top-5 pharma company's biotech partnership ecosystem with more than 100 biopharma partners and over 3 million inference runs; infrastructure for a national cancer research alliance adding 8 or more academic medical centers in 2026; a health system deployment that harmonized 600 million records with standardized data available to more than 4,000 projects; and an EU osteoarthritis research consortium of 450 partners (39 OA consortium partners) covering data on 70 million individuals. Press coverage of the May 2025 Series A cited named initiatives with the FAITE Biopharma Consortium, Sheba Medical Center, and a Google and Swift fraud-prevention effort, and reported roughly 20 employees.

Latest developments

Recent product emphasis is on agentic AI: an MCP server allows plain-English querying of data and construction of governed agentic workflows that run where the data lives, alongside GPU-accelerated workloads across multi-cloud and hybrid environments. The company also announced the inaugural Federate AI Summit for October 19-20, 2026, and cites 2026 expansion of a national cancer research alliance deployment to additional academic medical centers.