A new generation of diagnostic technology aiming to transform the early detection of coronary artery disease has secured significant backing, as UK investors join a multimillion-dollar bet on artificial intelligence’s power to predict heart attacks.
The startup HEARTio has closed a $4.25 million seed funding round with participation from investors including Audacious Capital, Bessel, Intelligence Ventures, LifeX, and VU Venture Partners. The capital will propel the company’s ECGio diagnostic platform towards critical clinical trials and a submission for US Food and Drug Administration (FDA) clearance.
The personal loss behind a public health mission
The company’s drive stems from a deeply personal tragedy for its co-founder and CEO, Utkars Jain. As a teenager, he learned how his grandfather died after a misdiagnosis: hospital doctors treated chest pain as a suspected heart attack with blood thinners, only to discover the actual cause was a bleeding stomach ulcer. The anticoagulant treatment proved fatal.
“It clearly elucidated that illness not only impacts the person, but their family, and their family’s family,” Jain stated, adding that he also witnessed his father recover from a haemorrhagic stroke. This experience cemented a mission to improve decision-making at the earliest point of care, a vision he shares with fellow University of Pittsburgh alumni and co-founders Adam Butchy and Michael Leasure.
Mining routine data for hidden warnings
Heart disease remains the leading cause of death in the United States, with approximately 6.7 million American adults living with heart failure. A silent, pre-symptomatic phase known as “Pre-Heart Failure” (Stage B) affects roughly 34% of them—about two million people—where structural damage has begun but often goes undetected.
Current diagnostic methods for coronary artery disease (CAD) frequently involve invasive cardiac catheterisation or imaging with contrast dyes or radiation. These are costly, time-consuming, and typically reserved for patients already showing clear symptoms.
HEARTio’s approach is to extract far more information from a test that is already ubiquitous: the standard 12-lead electrocardiogram (ECG). Its ECGio platform uses deep learning algorithms to analyse ECG signals, identifying patterns associated with CAD. The system aims to predict the presence, severity, and location of coronary blockages, providing insights comparable to invasive procedures but without catheters, radiation, or dye.
The company states its platform can take any 12-lead ECG and, using AI, determine if a patient experiencing pain is at low or high risk of CAD. It is designed as a “headless API” that integrates into existing clinical infrastructure without requiring new hardware or extra steps in a physician’s workflow.
Validation in major cardiology journals
Early research supporting the technology has been published in prominent medical journals. A study in the Canadian Journal of Cardiology demonstrated that a deep learning model could predict angiographic coronary artery disease using only ECG data from stable patients.
A larger, more recent study involving over 16,000 patients, published in JACC Advances in January 2026, further validated the model. That research assessed its ability to predict clinically significant CAD in patients undergoing coronary angiography. In external validation, the model achieved a positive predictive value of 82.5% and a negative predictive value of 88.1%.
This scientific groundwork is being expanded through a partnership with the Allegheny Health Network (AHN) for a large-scale study intended to validate ECGio in a general population and pave the way for the company’s pivotal FDA study.
Navigating a competitive field with a clear differentiator
The competitive landscape for cardiac diagnostics includes companies using CT scans, such as Cleerly and Heartflow, other ECG-based tools like Anumana and Powerful Medical, and firms using proprietary hardware, including Corvista and Genetesis.
Jain told TFN that while some are seen more as partners, HEARTio’s key differentiator is its use of “pre-deployed hardware” and seamless integration. “It uses pre-deployed hardware, a headless API, no extra steps in the workflow to provide information that usually requires catheters, dyes, and radiation,” he stated.
The potential of the approach has been recognised with an FDA Breakthrough Device designation granted in 2020 and the co-founders being named to the Forbes 30 Under 30 list for Healthcare in 2024.
The road to market and beyond
With the new funding secured, HEARTio’s immediate goals are clear. “Our major goals are to complete our pivotal study, submit to the FDA, generate revenue, and expand our product suite to other indications,” Jain said, listing potential expansions into PET-CT analysis, FFR prediction, and Coronary Calcium scoring.
The longer-term vision involves moving from the clinic to continuous monitoring. The company envisions its technology evolving to analyse ECG data streamed from wearable devices, providing physicians with ongoing updates on a patient’s cardiac health.
“This successful round of financing is a testament to the momentum we are building in bringing ECGio to market,” said Jain. “Our technology has the potential to democratise cardiovascular care and help create a world where no one experiences a heart attack.”
