Cardio.AI Platform
State-of-the-art ECG analytics technology. Extended ECG analysis as a service for your precise diagnostic assessment – fast, reliable, simple!
Automatic annotation and interpretation of ECG recordings of any lead configuration and duration of up to 35 days

State-of-the-art ECG analytics technology. Extended ECG analysis as a service for your precise diagnostic assessment – fast, reliable, simple!
Complete remote monitoring solution, we thought of everything end to end so that you can focus on your patients — and on building a world-class cardiovascular program.
Explore the comprehensive details of our successful initiation of multiple pilot projects in the realm of remote online monitoring.
The Cardio.AI team collaborates with a wide range of healthcare providers to ensure our services reach the people who need them most.
Advancing Heart Health Through AI Innovation
End-to-end services were provided
Already actively used by partner clinics in Ukraine
Long-term ECG reports delivered — and counting
Our mission is to develop products
to tackle real-world problems using cutting-edge advances in artificial
intelligence.
Those who used Cardio.AI monitoring service appreciated its ability to find business partners.
1. Access to the cloud-based ECG analytical Cardio.AI™ Platform for cardiac analysis designed to be used by ECG technicians and cardiologists. 2. Comprehensive end-to-end solution for remote cardiac Holter service for clinics with single-use ECG biosensors.
Please submit a request through the website's feedback form, indicating specifically which services you need.
The ECG biosensor is FDA, CE Mark certified. Cardio.AI™ Platform: we have successfully obtained CE MDR certification, and we are now working toward FDA clearance, which we expect to achieve in 2026.
Wellness devices, e.g. AppleWatch, SmartWatches, ECG Cardiograph.
Bittium, Cortium, LifeSignals, Livetec, Philips, Biomedical Instruments (BI), BTL, ScottCare Holter, Amedtec.
We process ECG signals from any ECG device, but the quality of AI-pass somehow depends on the quality of the device's output. In some cases adding the data from the device to the training set is required, especially for devices with very specific noise. You need to export ECG data and send us a few examples from your device in the following formats: EDF, BDF, SCP, and ZHR to check for processing quality. Please ensure the channels have proper names (I, II, V5, AFR) — which the neural network requires to process the intra-ventricular blocks properly. Channel names could be approximate if those are modified leads. The supported channel names are I, II, III, AVL, AVR, AVF, V1, V2, V3, V4, V5, V6, ES, AS, and AI.
The Cardio.AI Platform supports files in the following types: EDF, BDF, SCP, and ZHR. To prepare EDFs, use libs like EDFlib or PyEDFlib (if you use Python).
Yes, it is possible. Send us the appropriate request through the feedback form on the site.
Cardiologists, cardiologist-technicians, medical staff.
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