The Careflow Platform
Careflow is an AI assisted operating platform for data flow orchestration, visualization, and observation. It interconnects healthcare data systems and AI models to support clinical decisions across the patient continuum of care. It provides a comprehensive timeline of the patient's health journey and offers data observability to ensure trust in AI-driven healthcare.
Use Cases
Vendor Developers & Hospital Informatics
Onboard and configure data sources, models, and applications. Data bundle setup, manage integrations with hospital systems, and deployment settings.
Clinicians & Researchers
Leverage orchestrator analytics, deployment status metrics, and model output tracking to evaluate performance over time. Interact with the deployed application through visualizations such as timelines and insights dashboards.
Careflow Documentation
Careflow Documentation is the central hub for everything you need to onboard, integrate and deploy. Explore the different use cases and tools designed to help vendor developers, hospital informatics, researchers and clinicians streamline clinical workflows and data management.
Within the documentation, you will find step-by-step guides to walk you through different use cases, from onboarding new patient profiles to consolidating data across connected devices and applications.
Vendor Developers
Vendor Developers are responsible for onboarding and configuring data sources, models, and applications. They define inputs and outputs, compute specifications, and upload necessary configuration or integration files (e.g., Mirth files). They also determine whether outputs should be displayed in CareFlow and configure any additional display settings. Their role ensures the technical components are correctly packaged and ready for deployment within the system.
Hospital Informatics
Hospital Informatics teams focus on implementing and operationalizing the solution within the healthcare environment. They support data bundle setup, manage integrations with hospital systems, and help configure deployment settings through tools like the Orchestrator. They ensure compliance, data governance, access control, and analytics monitoring are properly configured so the solution runs securely and efficiently in production.
Researchers
Researchers primarily engage with the platform through its analytics and monitoring capabilities. They use orchestrator analytics, deployment status metrics, and model output tracking to evaluate performance over time.
Clinicians
Clinicians interact with the deployed application through visualizations such as timelines and insights dashboards. They use model outputs to inform clinical decision-making within their workflow.