Customer challenge

  • Enable legacy imaging devices with advanced capabilities such as AI/ML, data aggregation and analytics
  • Aggregate data from various sources including point-of-care medical devices
  • Zero impact on existing devices and systems in a hospital
  • Near real-time analysis and outcomes


  • Develop a platform for imaging devices with feature-rich capabilities
  • Future roadmap for the platform with product release alignments
  • Support data protocols
  • Enable platform to support different deployment models based on product needs
  • Support product team with queries and possible defects


  • A cloud native edge compute environment with GPUs to run clinical applications
  • Customizable, purpose-built, modular software platform based on cloud-native technology (Kubernetes)
  • Deployment of healthcare solutions to aggregate, correlate, analyze, and process data from connected medical devices (hardware & software)
  • An orchestrator to create and execute algorithm pipelines
  • On-prem, data center, and cloud deployment


  • Healthcare-specific services – DICOM services, HL7
  • Imaging modality apps – visualization, collaboration, scanner configuration management, etc
  • Gateway – a data aggregator for point of devices
  • Algorithm orchestrator – to run AI models and algorithms
  • Cloud connectivity
  • Remote serviceability


  • Reduced time for the development of healthcare applications leveraging platform capabilities
  • Readily available capabilities to realize functionalities without infrastructure concerns


Clinical workflow 

  • Improved imaging workflow with AI/ML algorithms in near real-time
  • Data aggregation for remote patient monitoring
  • Access to patient data from multiple sources

Digital Health Platform 

  • Microservices-based architecture
  • Multiple deployment models – On-prem | data center | cloud
  • Scalable services to run on small to very large computing environments
  • Enabling third-party application development