Rhino Federated Computing Launches Trusted Integrations and Workflows for Enterprise AI

BOSTON, Oct. 22, 2026 /CourierPR/ -- Rhino Federated Computing has unveiled two new capabilities, Trusted Integrations and Workflows, designed to transform federated AI from a pilot project into a fully operational enterprise program. These tools are part of the company's ongoing efforts to make AI more accessible and effective for businesses across various industries, particularly in healthcare and life sciences.

According to a recent analysis by Rhino Federated Computing, research on federated learning has seen a significant surge, growing more than 13-fold since 2020. Healthcare and life sciences are emerging as the fastest-growing application areas for this technology. However, scaling federated AI from a pilot to a production environment presents unique challenges. A pilot typically operates in isolation, using hand-written scripts and data that cannot move freely. In contrast, a production program must integrate with existing enterprise technology, ensuring data privacy and security while maintaining transparency and governance.

Trusted Integrations allow enterprises to leverage their existing technology infrastructure within the Rhino Federated Computing Platform (FCP). Each Rhino Client is designed to establish a secure, approved connection to internal and external systems, including FHIR servers, cloud data platforms, databases, and managed health data services. This ensures that data remains under the control of the enterprise, with data moving only as necessary and only through the approved channels. The connection remains open only during the execution of the required code, ensuring minimal risk and maximum compliance.

Workflows, on the other hand, automate multi-step federated processes, enabling teams to build, share, and run these processes across different sites and projects. This is particularly useful in research networks, where a single cohort-building Workflow can be deployed across multiple hospitals, streamlining data refreshes and the addition of new sites. The consistency of these workflows ensures that differences in results are attributable to local data variations rather than procedural discrepancies. Every Workflow run records the exact pipeline executed, including task logs and outputs, providing a comprehensive audit trail for governance and compliance.

These new capabilities extend Rhino's existing solutions, such as Rhino Data Activation and Rhino Federated Intelligence. For instance, a drug discovery consortium can deploy fine-tuned models through each member's private model serving environment, ensuring that sensitive data remains secure while still benefiting from collaborative AI. Similarly, a hospital can harmonize refreshed clinical data locally with Rhino’s Data Harmonization Engine, then send only an approved FHIR payload to the FHIR server of its choice. A bank can prepare AI-ready datasets and send fraud assessments to the systems its investigators already use, all while maintaining strict control over data and processes.