Proprietary deep learning models trained on millions of ECGs analyse cardiac signals in real-time, improving ECG interpretation.
Proprietary neural networks trained on one of the largest ECG datasets in the world, delivering medical-grade pattern recognition across cardiac conditions.
Flexible deployment on device or in the cloud, enabling rapid clinical decision-making at the point of care.
Comprehensive evaluation across all 12 ECG leads for complete cardiac rhythm assessment and diagnosis.
Accurately identifies atrial fibrillation, ventricular tachycardia, SVT, and other rhythm abnormalities, on par with board-certified cardiologists.
Early detection of heart attacks and ischaemic events through advanced ST-segment and morphology analysis, enabling faster time to treatment.
Comprehensive, clinician-ready reports with structured diagnostic findings, interval measurements, and per-condition confidence scores.
Seamlessly connects to existing electronic medical record systems, ensuring AI-powered insights flow directly into clinical workflows.
The most comprehensive AI-powered ECG interpretation available. PulseAI detects over 100 conditions across rhythms, conduction, infarction, ischaemia, hypertrophy, and more, with lead-specific measurements and confidence scores for every finding.