BOSTON, Oct. 22, 2026 (GLOBE NEWSWIRE) -- At the Federate AI Summit, Rhino Federated Computing announced Trusted Integrations and Workflows, two capabilities on the Rhino Federated Computing Platform (FCP) that that turn federated AI pilots into production programs built on the enterprise’s existing technology.
Published research on federated learning has grown more than 13-fold since 2020, and healthcare and life sciences is its fastest-growing application, according to a Rhino Federated Computing analysis of the OpenAlex research database. That body of work has settled whether AI can run on data that cannot move. Scaling it poses a different problem.
A pilot runs on one team, one dataset, and hand-written scripts, walled off from the rest of the enterprise. A program must repeat that work for every project at every site, draws on the data platforms and systems the enterprise already runs, and answers to stakeholders who ask what ran, what left each site, and what resulted. When every initiative means rebuilding by hand and every connection requires a security exception and custom integration, programs stall at the pilot. Agentic AI raises the stakes further: no enterprise will let AI act on its data until those actions are scoped and reviewable.
Trusted Integrations lets enterprises put the technology they already own to work on federated projects. Each Rhino Client is built to open an approved, scoped connection to systems inside the customer's secure perimeter, from FHIR servers and cloud data platforms to databases, object stores, private model serving, secrets managers, and managed health data services.
Customers keep control of their source data and networking. Data can move in either direction: a team can pull source data from a cloud data platform into the Rhino Client, or send approved context to a private model endpoint for an AI agent. Only what the integration allows crosses the connection, and the connection stays open only while the code that needs it runs.
Workflows turn multi-step federated work into software that teams build once, share, and run everywhere. A research network, for example, can publish one cohort-building Workflow and run it at every member hospital, so a data refresh or a twentieth site no longer requires starting over. Because each site runs identical steps, differences in results reflect the local data, not the method. Every Workflow run records the exact pipeline it executed, with each task's logs and outputs, so governance is embedded. The same structure makes Workflows a natural boundary for AI agents, which act only through steps a team has defined and can review.
Together, the two capabilities extend Rhino Data Activation and Rhino Federated Intelligence, the single-party and multi-party solutions built on the Rhino FCP. A drug discovery consortium can deploy fine-tuned models through each member's private model serving environment. 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.
"Our customers have proven that federated AI works, so their ambitions are growing. They want it to draw on the technology they’ve already invested in and to deliver value continuously," said Antoni Abella Vendrell, VP of Product for Rhino Federated Computing. "Trusted Integrations and Workflows give our enterprise customers the automation and direct access to core systems to run federation within an enterprise context."
Trusted Integrations and Workflows are available now to Rhino FCP customers. To see both in action, request a demo with the experts at Rhino.
About Rhino Federated ComputingRhino Federated Computing is a leader in commercial-grade federated AI and computing. We enable highly-regulated enterprises to activate the full value of sensitive data with full privacy preservation across internal and external silos. Our customers can run any workload, from analytics and model training to agents and AI, across their federated intelligence networks with complete transparency, control, and governance. By bringing code to the data rather than centralizing sensitive information, Rhino empowers life sciences, healthcare, financial services, and other industry leaders to collaborate securely, accelerate innovation, and deploy impactful AI at scale. To learn more, please visit www.rhinofcp.com or follow us at www.linkedin.com/company/rhinofc/.
For more information, press only: Renee Hurley, Rhino Federated Computing, renee@rhinofcp.com
