Rhino Federated Computing Platform

What it does

Rhino Federated Computing Platform (FCP) is enterprise software for processing, harmonizing, and analyzing data across distributed environments. It is intended for organizations working with fragmented or sensitive data, with documented use in healthcare, life sciences, financial services, and the public sector. The platform brings computation to data rather than requiring it to be centralized, and supports federated learning and inference as well as analytics and data workflows.

Teams register datasets, create projects and collaborators, then run Python, generalized-compute or NVFlare code across participating environments. The Python SDK calls the authenticated FCP API; the MCP server lets compatible assistants request federated analytics and code execution with platform permissions. Start with a demo, provision an account and configure an online FCP Client. Establish data access, permissions and compute requirements before running workloads.

What it can do

• Federated learning and model inference across distributed data
• Dataset registration, configuration, and federation
• Data schema creation and management
• Data harmonization and transformation, including FHIR use cases
• Execution of Python, generalized-compute, and NVFlare code
• Project, collaborator, and code-run management

Works with

• FHIR
• NVFlare
• DICOMWeb
• Rhino SDK
• Rhino MCP Server

Before you choose

• Confirm commercial terms and deployment prerequisites with Rhino.
• Participating environments need appropriate data permissions and governance.
• Review code, aggregate outputs and model results before using them in clinical or operational decisions.

Listed under

• Data
• AI agents
• Clinical data harmonization
• Data collaboration
• Enterprise
• Federated computing
• Federated learning

Get started

The homepage directs prospective users to request a demo.

1. Request a demo and arrange account access.
2. Install and configure the FCP Client; verify that it is online and the environment is ready.
3. Create a project and permissions, connect data sources and register datasets. Use the UI, authenticated Python SDK/API or MCP integration for the chosen workflow.

Rates, billing basis and included services need confirmation.

We couldn’t find published prices for Rhino Federated Computing Platform.

Sources for this overview

Product pages, documentation, and pricing checked 2 Nov 2026. Each source supports part of the overview; availability and prices can change.

• About Rhino FCP | Trusted Research Environment ↗www.rhinofcp.com
• Rhino FC | Activate Sensitive Data for AI, Analytics, and Agents ↗www.rhinofcp.com
• What is the Rhino SDK? | RhinoFCP Docs ↗docs.rhinofcp.com
• Quick Start Guide | RhinoFCP Docs ↗docs.rhinofcp.com
• MCP Getting Started | RhinoFCP Docs ↗docs.rhinofcp.com
• Rhino FC | Activate Sensitive Data for AI, Analytics, and Agents ↗www.rhinofcp.com
• About Rhino Federated Computing | RhinoFCP Docs ↗docs.rhinofcp.com

Company website

rhinofcp.com: product, pricing and policy pages

YC directory mirror

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Human review

Checked by a person

knowledge_base

manual_review

Last checked 2 Nov 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.