Build

Build Your Radiology AI Solution Seamlessly on deepcOS

Bridge the gap between AI research and clinical application on one comprehensive platform.

From Research to Production

With its Build functionality and cloud native foundation, deepcOS is optimized to support the entire AI development process from research to production. Whether you're a medical researcher looking to validate and deploy your AI model in your own clinical environment or an AI vendor aiming to more quickly expand your market reach, the deepcOS platform offers a robust solution to align cross-functional stakeholders and overcome complex engineering challenges, allowing you to focus your efforts on your AI model’s performance.

For AI development, deepcOS delivers

Standardization of processes and interfaces to bridge the gap between cross-functional teams, facilitating better collaboration and integration of in-house AI solutions in clinical settings.

A core foundation to package AI models appropriately for clinical use, including MONAI MAPs compatibility, with the potential to help streamline the regulatory approval process

Real-time deployment of AI models in live clinical environments with mechanisms for continuous monitoring and maintenance, ensuring safe and effective performance.

A vendor-neutral platform, meaning there are no proprietary interests to restrict which AI solutions are submitted.

 
 
 
 
 

Self-service integration of your AI models in real-time

Move your AI model from development to clinical practice without challenges from backend engineering and IT prioritizations.
 

Compatibility with MONAI MAPs

MONAI framework allows developers to rapidly prototype, train, and deploy AI models for medical imaging applications. With MONAI MAPs containers, AI models are seamlessly delivered via deepcOS’ Build workflow.
 

Transparency in integration

See all of your submissions at a glance and access tooling to troubleshoot submissions in real-time
 

Insights into your AI solution’s performance

Comprehensive dashboard enables users to monitor submitted AI solutions, gaining insights into execution time, success rate, and JSON-related metrics.

Looking to deploy your research AI engine?

Resources

AI Safety White Paper  

A comprehensive strategy for ensuring AI safety from pre- to post-deployment. Download

deepc joins King’s Health Partners Digital Health Hub

deepc will share its expertise with AI-focused medtech startups, helping them scale quickly and avoid first-time regulatory and technical pitfalls.
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Cloud or On-Prem?

Navigating AI deployment includes determining the best setup for your clinical organization. See what factors are involved in choosing between a cloud and on-prem platform.
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