Kardi AI Raises €5.3M at €23M Valuation to Detect Heart Rhythm Problems Earlier

Czech startup Kardi AI raises €5.3 million led by Callisto Health to expand AI-powered ECG monitoring and develop predictive cardiac risk models.

The Czech startup combines wearable ECG technology with AI analysis to identify intermittent cardiac rhythm abnormalities.

Kardi AI has raised €5.3 million in a Series A led by German healthtech investor Callisto Health, reaching a reported valuation of €23 million.

The financing also includes Česká spořitelna and Slovenská sporiteľňa through their Seed Starter programs, alongside BrightCap Ventures, Purple Ventures, DEPO Ventures and Garage Angels.

Founded in the Czech Republic in 2022, Kardi AI develops technology for long-term heart rhythm monitoring.

The company is led by CEO Vlastimil Hrabal.

Finding Problems That Short Tests Can Miss

Traditional electrocardiogram examinations often capture heart activity over a limited period.

Some arrhythmias occur intermittently and may not appear during a routine medical appointment.

Kardi AI combines a wearable chest strap with an ECG sensor, a mobile application and AI analysis.

Users can record heart activity over longer periods and share relevant information with medical professionals.

The system is designed to assist clinical assessment rather than independently replace a physician's diagnosis.

Expanding Beyond Central Europe

Kardi AI reports more than 6,000 users and relationships with over 70 hospitals in the Czech Republic.

The company already operates in several Central and Eastern European markets and plans further expansion.

Germany is a priority, while India, the United Arab Emirates and Singapore represent additional target markets.

The company has secured regulatory permissions supporting expansion into India and the UAE.

From Detection to Prediction

Kardi AI is also developing models intended to estimate the risk of future cardiac rhythm problems.

Such capabilities could eventually shift monitoring from detecting existing abnormalities toward identifying patients who may require closer observation.

However, predictive models still require clinical validation and any applicable regulatory approvals before routine medical use.

The new funding will support international expansion, product development and research.

Its challenge is to demonstrate reliable performance across diverse patient populations while integrating its technology into established healthcare workflows.

Sources: The Recursive; Tech.eu; EU-Startups interview.

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