Rhino Federated Computing

Founded by Ittai Dayan in 2021

Run federated machine learning and analytics across decentralized sensitive data without moving it

Pricing model

Demo

Rating

★ People love it

Time to value

Moderate Setup (1-3 hours)

You can use Rhino to run distributed artificial intelligence and analytics across sensitive datasets without moving raw files out of secure environments. It allows organizations to connect disparate data sources across multi-cloud and hybrid networks to train machine learning models collaboratively. The system includes a data harmonization engine that converts clinical records into standardized formats like FHIR. You can also build agentic workflows, deploy model inference across decentralized partner ecosystems, and query distributed databases using natural language protocols.

What Rhino Federated Computing does

Harmonize messy clinical records to FHIR standardsTrain machine learning models across decentralized nodesExecute distributed GPU-accelerated computing workloadsQuery sensitive data via Model Context ProtocolMonitor federated model inference runs across partner institutionsManage secure data access permissions across hybrid cloud setupsFederated computing infrastructure across hybrid and multi-cloud environmentsClinical data harmonization into standardized FHIR modelsDecentralized model training without transferring raw sensitive dataGPU-accelerated workload execution across distributed partner nodesGoverned AI agent deployment with plain English queries via MCPSecure distributed model inference tracking and validation

Pricing breakdown

Pricing model: Book a demo

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