
Juno Medical
Modern primary care powered by an intelligent clinical operating system for holistic patient management.

The AI platform for value-based care optimization and patient risk prediction.

ClosedLoop is an industry-leading healthcare data science platform engineered to accelerate the development and deployment of predictive models specifically for clinical and financial outcomes. By 2026, it has established itself as the dominant player in the Value-Based Care (VBC) ecosystem, offering a purpose-built AutoML engine that handles the nuances of longitudinal healthcare data, including EHR records, claims, and Social Determinants of Health (SDoH). The platform's technical architecture is centered around its Healthcare Data Model (HCDM), which automates the feature engineering process for thousands of clinical variables. This allows healthcare organizations to move beyond generic risk scores to high-performance, explainable models that identify rising-risk patients, predict hospital readmissions, and optimize resource allocation. ClosedLoop distinguishes itself through its focus on transparency and clinical validation, providing 'Acre'—an explainability toolkit that translates complex model outputs into actionable clinical insights for frontline providers. In the 2026 market, it is primarily utilized by large health systems, payers, and ACOs looking to reduce the Total Cost of Care (TCOC) while improving health equity through rigorous bias detection and mitigation tools.
ClosedLoop is an industry-leading healthcare data science platform engineered to accelerate the development and deployment of predictive models specifically for clinical and financial outcomes.
Explore all tools that specialize in predict patient risk. This domain focus ensures ClosedLoop delivers optimized results for this specific requirement.
Explore all tools that specialize in improve patient outcomes. This domain focus ensures ClosedLoop delivers optimized results for this specific requirement.
Explore all tools that specialize in risk stratification. This domain focus ensures ClosedLoop delivers optimized results for this specific requirement.
Proprietary automated machine learning engine optimized for sparse, longitudinal healthcare data sets.
A clinical-first explainability framework that identifies the specific factors driving an individual patient's risk score.
Integrated auditing tools to detect and mitigate algorithmic bias across demographic and socioeconomic lines.
Pre-built connectors for third-party social determinants data, including zip-code level economic indicators.
Direct support for HL7 FHIR standards for real-time data streaming and interoperability.
A library of 100+ pre-vetted clinical model templates for common conditions (CHF, COPD, Diabetes).
Bi-directional integration that pushes risk scores and clinical insights directly into Epic, Cerner, or Meditech.
Data discovery and mapping of historical claims and EHR data sources.
Establishing secure VPN or cloud-to-cloud connection (AWS/Azure).
Configuration of the Healthcare Data Model (HCDM) for ingestion.
Automated feature engineering across clinical and SDoH variables.
Initial model training using ClosedLoop AutoML specialized for healthcare.
Clinical validation of model outputs with subject matter experts.
Bias audit and health equity assessment using built-in fairness toolkits.
Integration with workflow tools via SMART on FHIR or custom APIs.
Pilot deployment for specific care management teams.
Full-scale production monitoring and automated model retraining cycles.
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