9+1AI provides an AI engine that analyzes 12‑lead and single‑lead ECGs to generate quantitative risk scores for hidden cardiovascular conditions. Trained on over 10 million ECGs and externally validated, the platform delivers real‑time results via a HIPAA‑compliant REST API for integration with EHRs, telehealth systems, and consumer health applications, enabling clinicians to target further testing and interventions.
Funding
Funding not disclosed
Founders
Product
Problem
Clinicians often rely on standard ECG interpretation, which can miss subtle, subclinical cardiovascular abnormalities that precede overt disease. This gap limits early risk stratification and delays preventive interventions for patients who appear normal on conventional analysis.
Solution
9+1AI delivers an artificial‑intelligence engine that processes any 12‑lead or single‑lead ECG to generate quantitative risk scores for hidden cardiovascular pathology. The model is trained on more than 10 million ECGs and has undergone external clinical validation, ensuring robustness across diverse populations. Results are returned in real time via secure RESTful APIs, enabling seamless embedding into hospital information systems, telehealth platforms, and consumer health applications. By surfacing diagnostic and prognostic insights, the platform guides targeted ordering of echocardiograms, laboratory panels, and follow‑up procedures, supporting more precise clinical decision‑making. The solution is designed for both enterprise health networks and direct‑to‑consumer use cases, with built‑in PHI encryption and compliance with FDA Breakthrough Device designation requirements.
Target Audience
Primary users include cardiology and primary‑care clinicians, health‑system IT teams, telehealth providers, and developers of consumer health wearables seeking AI‑enhanced ECG analytics.
Features
- Deep‑learning ECG model trained on >10 M de‑identified recordings, with external validation cohorts demonstrating high sensitivity for subclinical disease
- Real‑time inference engine accessible through HIPAA‑compliant RESTful API, supporting Category III billing codes
- Automated risk scoring and structured report generation for diagnostic (e.g., silent ischemia) and prognostic (e.g., future heart failure) outcomes
- Compatibility with medical‑grade ECG devices, health‑system EHRs, telehealth platforms, and mobile consumer applications
- Secure data handling pipeline with end‑to‑end encryption, role‑based access controls, and audit logging
- Ability to analyze retrospective ECG archives to identify at‑risk patients for proactive outreach
- Scalable cloud infrastructure that maintains low latency (<200 ms) per ECG for high‑throughput environments