Federated Data Science
Do data science where data lives
Run the full data science stack — exploration, data preparation, analysis, model training, validation, and inference — across distributed data environments with full control and compliance.
The Problem
Data science teams at regulated enterprises expend enormous efforts negotiating bilateral data sharing agreements before a single exploration gets run or a single model gets trained. Teams end up building with the data they can access rather than the data they need — producing narrower models, weaker results, and delayed programs. The bottleneck is not capability. It is data access.
Why Rhino
Access
Work with data you could never centralize both inside and outside your four walls
Speed
Compress months of negotiation to weeks of deployment
Scale
Build models or run analysis on larger, more diverse, multi-modal datasets
Complaince
Satisfy data governance, privacy regulations, IP protection, and contractual obligations out of the box
What Rhino Makes Possible
Federated Analytics — Explore and learn from privacy-protected data. Control what other sites see down to the row level. No raw data leaves its source.
Federated Inference — Run models across data sites on a continuous basis. Enable real-time decisions at the edge. Extend the operational reach of AI into new domains.
Federated Learning — Build better models with more diverse data. Train models and run inference with a single click. Harmonize data across sites to streamline data prep.
Platform Power
Rhino’s Federated Computing Platform undergirds every solution and customer success we deliver.
Compliant by Design
Audit-ready logging across every action and activity
Multi-Level Security and Privacy Protection
All the basics, and differential privacy, enterprise key management, confidential computing, and more thrown in
Open and Agnostic
Bring your own cloud, bring your own tech stack
Secure MCP Server
We just launched the world's first secure MCP for federated computing. Use plain language to explore data across sites, perform semantic and syntactic data harmonization, train models, and run inference – all without writing a single line of code.
