Predictive Heart
Disease
Predictive
Heart
Disease
PARTNERS
PARTNERS
PARTNERS
Our clinical partners validate the science and accelerate life-saving cardiovascular innovation.
ARTIFICIAL INTELLEGENCE
ARTIFICIAL INTELLEGENCE
ARTIFICIAL INTELLEGENCE
Platform
AEGIS ®
AEGIS ®
Phase 1
Foundation
Risk Prediction: Multi-Modal Cardiovascular Assessment
3D Visualization: Interactive Heart Modeling & Risk Mapping
Panel: Tech for Good: Building with Purpose
Intelligence
AI Analytics: Real-Time Risk Stratification Engine
Clinical Insights: Evidence-Based Treatment Recommendations
Population Health: Comprehensive Patient Management Dashboard
Deployment
Hospital Trials: Validation with Leading Medical Centers
FDA Pathway: Regulatory Clearance & Clinical Evidence
Enterprise Launch: Scalable Healthcare System Integration
Phase 2
Advanced
Digital Twins: Patient-Specific Cardiovascular Simulation
4D Flow Analysis: Real-Time Hemodynamic Modeling
Treatment Optimization: Virtual Therapy Testing & Outcomes
Innovation
Predictive Medicine: 5-10 Year Event Forecasting
Personalized Care: Genomic-Informed Risk Assessment
Remote Monitoring: Continuous Wearable Data Integration
Evolution
Pharma Partnerships: Virtual Clinical Trial Platform
Drug Discovery: Cardiovascular Therapy Development
Global Expansion: International Healthcare Deployment
Phase 1
Foundation
Risk Prediction: Multi-Modal Cardiovascular Assessment
3D Visualization: Interactive Heart Modeling & Risk Mapping
Panel: Tech for Good: Building with Purpose
Intelligence
AI Analytics: Real-Time Risk Stratification Engine
Clinical Insights: Evidence-Based Treatment Recommendations
Population Health: Comprehensive Patient Management Dashboard
Deployment
Hospital Trials: Validation with Leading Medical Centers
FDA Pathway: Regulatory Clearance & Clinical Evidence
Enterprise Launch: Scalable Healthcare System Integration
Phase 2
Advanced
Digital Twins: Patient-Specific Cardiovascular Simulation
4D Flow Analysis: Real-Time Hemodynamic Modeling
Treatment Optimization: Virtual Therapy Testing & Outcomes
Innovation
Predictive Medicine: 5-10 Year Event Forecasting
Personalized Care: Genomic-Informed Risk Assessment
Remote Monitoring: Continuous Wearable Data Integration
Evolution
Pharma Partnerships: Virtual Clinical Trial Platform
Drug Discovery: Cardiovascular Therapy Development
Global Expansion: International Healthcare Deployment
Phase 1
Foundation
Risk Prediction: Multi-Modal Cardiovascular Assessment
3D Visualization: Interactive Heart Modeling & Risk Mapping
Panel: Tech for Good: Building with Purpose
Intelligence
AI Analytics: Real-Time Risk Stratification Engine
Clinical Insights: Evidence-Based Treatment Recommendations
Population Health: Comprehensive Patient Management Dashboard
Deployment
Hospital Trials: Validation with Leading Medical Centers
FDA Pathway: Regulatory Clearance & Clinical Evidence
Enterprise Launch: Scalable Healthcare System Integration
Phase 2
Advanced
Digital Twins: Patient-Specific Cardiovascular Simulation
4D Flow Analysis: Real-Time Hemodynamic Modeling
Treatment Optimization: Virtual Therapy Testing & Outcomes
Innovation
Predictive Medicine: 5-10 Year Event Forecasting
Personalized Care: Genomic-Informed Risk Assessment
Remote Monitoring: Continuous Wearable Data Integration
Evolution
Pharma Partnerships: Virtual Clinical Trial Platform
Drug Discovery: Cardiovascular Therapy Development
Global Expansion: International Healthcare Deployment
FAQ
FAQ
FAQ
FAQ
Still got questions? Feel free to reach out. We're happy to help.
What is AEGIS AI and how does it work?
AEGIS (Advanced Evidence-Guided Intelligence System) is a cardiovascular digital twin platform that creates living, real-time replicas of patients' cardiovascular systems. By integrating multi-modal data from ECG, medical imaging, genomics, wearables, and clinical records, AEGIS uses physics-based modeling and AI algorithms to predict cardiovascular events 5-10 years before symptoms appear. The platform provides clinicians with actionable insights, treatment simulations, and personalized risk assessments—transforming cardiovascular care from reactive to predictive.
How accurate are AEGIS predictions?
AEGIS achieves over 90% accuracy in predicting major adverse cardiovascular events (MACE) including heart attacks, strokes, and heart failure. Our algorithms are trained on 500,000+ patient datasets and validated across 20+ hospital systems. The platform's predictions are backed by 183 peer-reviewed studies that establish digital cardiovascular twins as the scientific standard for predictive cardiology. Clinical trials show AEGIS reduces adverse events by 25% compared to traditional risk assessment methods.
How does AEGIS integrate with existing hospital systems?
AEGIS is built with healthcare interoperability in mind. The platform is HL7 FHIR-compliant and integrates seamlessly with major EHR systems including Epic, Cerner, and Allscripts. Implementation typically takes 4-8 weeks and includes data migration, staff training, and workflow optimization. Our API-first architecture allows real-time data exchange while maintaining HIPAA compliance and enterprise-grade security. AEGIS works within your existing clinical workflows—no system overhaul required.
What data does AEGIS require to generate predictions?
AEGIS works with tiered data inputs to accommodate different healthcare settings. Minimum requirements include basic patient demographics, vital signs, and standard lab results (cholesterol, blood pressure). Enhanced accuracy comes from adding ECG data, echocardiography, and medical imaging (CT/MRI). Optimal performance incorporates genetic data, wearable device information, and longitudinal health records. The platform adapts to available data—delivering value even with basic inputs while scaling accuracy as more data becomes available.
Is AEGIS FDA approved and how do you ensure clinical safety?
AEGIS is currently pursuing FDA 510(k) clearance as a clinical decision support software, with breakthrough device designation expected in 2026. Our development follows FDA's Software as a Medical Device (SaMD) guidelines with rigorous clinical validation. The platform includes built-in safety mechanisms: all predictions include confidence intervals, recommendations are guideline-aligned, and final treatment decisions remain with physicians. AEGIS augments—not replaces—clinical judgment. Our algorithms undergo continuous validation and are regularly updated based on real-world clinical outcomes
What is the expected ROI for hospitals implementing AEGIS?
Healthcare systems typically see ROI within 12-18 months through multiple value drivers: Cost reduction from preventing expensive cardiac events and hospitalizations (average savings: $15,000-50,000 per prevented event), Revenue optimization through improved risk stratification and appropriate intervention timing, Operational efficiency via reduced unnecessary testing and streamlined workflows, and Quality metrics improvements that impact value-based care reimbursements. Pilot hospitals report 25% reduction in adverse events, 30% decrease in unnecessary procedures, and improved patient satisfaction scores. We provide detailed ROI modeling during implementation planning.
What is AEGIS AI and how does it work?
AEGIS (Advanced Evidence-Guided Intelligence System) is a cardiovascular digital twin platform that creates living, real-time replicas of patients' cardiovascular systems. By integrating multi-modal data from ECG, medical imaging, genomics, wearables, and clinical records, AEGIS uses physics-based modeling and AI algorithms to predict cardiovascular events 5-10 years before symptoms appear. The platform provides clinicians with actionable insights, treatment simulations, and personalized risk assessments—transforming cardiovascular care from reactive to predictive.
How accurate are AEGIS predictions?
AEGIS achieves over 90% accuracy in predicting major adverse cardiovascular events (MACE) including heart attacks, strokes, and heart failure. Our algorithms are trained on 500,000+ patient datasets and validated across 20+ hospital systems. The platform's predictions are backed by 183 peer-reviewed studies that establish digital cardiovascular twins as the scientific standard for predictive cardiology. Clinical trials show AEGIS reduces adverse events by 25% compared to traditional risk assessment methods.
How does AEGIS integrate with existing hospital systems?
AEGIS is built with healthcare interoperability in mind. The platform is HL7 FHIR-compliant and integrates seamlessly with major EHR systems including Epic, Cerner, and Allscripts. Implementation typically takes 4-8 weeks and includes data migration, staff training, and workflow optimization. Our API-first architecture allows real-time data exchange while maintaining HIPAA compliance and enterprise-grade security. AEGIS works within your existing clinical workflows—no system overhaul required.
What data does AEGIS require to generate predictions?
AEGIS works with tiered data inputs to accommodate different healthcare settings. Minimum requirements include basic patient demographics, vital signs, and standard lab results (cholesterol, blood pressure). Enhanced accuracy comes from adding ECG data, echocardiography, and medical imaging (CT/MRI). Optimal performance incorporates genetic data, wearable device information, and longitudinal health records. The platform adapts to available data—delivering value even with basic inputs while scaling accuracy as more data becomes available.
Is AEGIS FDA approved and how do you ensure clinical safety?
AEGIS is currently pursuing FDA 510(k) clearance as a clinical decision support software, with breakthrough device designation expected in 2026. Our development follows FDA's Software as a Medical Device (SaMD) guidelines with rigorous clinical validation. The platform includes built-in safety mechanisms: all predictions include confidence intervals, recommendations are guideline-aligned, and final treatment decisions remain with physicians. AEGIS augments—not replaces—clinical judgment. Our algorithms undergo continuous validation and are regularly updated based on real-world clinical outcomes
What is the expected ROI for hospitals implementing AEGIS?
Healthcare systems typically see ROI within 12-18 months through multiple value drivers: Cost reduction from preventing expensive cardiac events and hospitalizations (average savings: $15,000-50,000 per prevented event), Revenue optimization through improved risk stratification and appropriate intervention timing, Operational efficiency via reduced unnecessary testing and streamlined workflows, and Quality metrics improvements that impact value-based care reimbursements. Pilot hospitals report 25% reduction in adverse events, 30% decrease in unnecessary procedures, and improved patient satisfaction scores. We provide detailed ROI modeling during implementation planning.
What is AEGIS AI and how does it work?
AEGIS (Advanced Evidence-Guided Intelligence System) is a cardiovascular digital twin platform that creates living, real-time replicas of patients' cardiovascular systems. By integrating multi-modal data from ECG, medical imaging, genomics, wearables, and clinical records, AEGIS uses physics-based modeling and AI algorithms to predict cardiovascular events 5-10 years before symptoms appear. The platform provides clinicians with actionable insights, treatment simulations, and personalized risk assessments—transforming cardiovascular care from reactive to predictive.
How accurate are AEGIS predictions?
AEGIS achieves over 90% accuracy in predicting major adverse cardiovascular events (MACE) including heart attacks, strokes, and heart failure. Our algorithms are trained on 500,000+ patient datasets and validated across 20+ hospital systems. The platform's predictions are backed by 183 peer-reviewed studies that establish digital cardiovascular twins as the scientific standard for predictive cardiology. Clinical trials show AEGIS reduces adverse events by 25% compared to traditional risk assessment methods.
How does AEGIS integrate with existing hospital systems?
AEGIS is built with healthcare interoperability in mind. The platform is HL7 FHIR-compliant and integrates seamlessly with major EHR systems including Epic, Cerner, and Allscripts. Implementation typically takes 4-8 weeks and includes data migration, staff training, and workflow optimization. Our API-first architecture allows real-time data exchange while maintaining HIPAA compliance and enterprise-grade security. AEGIS works within your existing clinical workflows—no system overhaul required.
What data does AEGIS require to generate predictions?
AEGIS works with tiered data inputs to accommodate different healthcare settings. Minimum requirements include basic patient demographics, vital signs, and standard lab results (cholesterol, blood pressure). Enhanced accuracy comes from adding ECG data, echocardiography, and medical imaging (CT/MRI). Optimal performance incorporates genetic data, wearable device information, and longitudinal health records. The platform adapts to available data—delivering value even with basic inputs while scaling accuracy as more data becomes available.
Is AEGIS FDA approved and how do you ensure clinical safety?
AEGIS is currently pursuing FDA 510(k) clearance as a clinical decision support software, with breakthrough device designation expected in 2026. Our development follows FDA's Software as a Medical Device (SaMD) guidelines with rigorous clinical validation. The platform includes built-in safety mechanisms: all predictions include confidence intervals, recommendations are guideline-aligned, and final treatment decisions remain with physicians. AEGIS augments—not replaces—clinical judgment. Our algorithms undergo continuous validation and are regularly updated based on real-world clinical outcomes
What is the expected ROI for hospitals implementing AEGIS?
Healthcare systems typically see ROI within 12-18 months through multiple value drivers: Cost reduction from preventing expensive cardiac events and hospitalizations (average savings: $15,000-50,000 per prevented event), Revenue optimization through improved risk stratification and appropriate intervention timing, Operational efficiency via reduced unnecessary testing and streamlined workflows, and Quality metrics improvements that impact value-based care reimbursements. Pilot hospitals report 25% reduction in adverse events, 30% decrease in unnecessary procedures, and improved patient satisfaction scores. We provide detailed ROI modeling during implementation planning.