A single human heart beats about one hundred thousand times a day. For a cardiologist looking at an echocardiogram, which is an ultrasound video of those moving chambers, interpreting those beats is a race against time, data, and human subjectivity. Every day, millions of cardiac ultrasound images are generated worldwide, yet the process of analyzing them has remained stubbornly manual for decades. Doctors sit at screens, clicking, measuring, and drawing lines on fuzzy grey moving images, tracing the boundaries of the heart to calculate vital metrics.
This manual process takes up to forty-five minutes per patient and leaves a massive twenty percent margin of variability between different clinicians reading the exact same scan. In a field where a few millimeters of structural difference can separate a healthy life from sudden heart failure, this lack of standardization is a critical bottleneck.
James Hare saw this systemic inefficiency not as an unchangeable medical reality, but as a data challenge waiting for an intelligent solution. As the co-founder and CEO of Us2.ai, Hare has stepped outside his traditional tech comfort zone to lead a medical technology revolution. By introducing a fully automated, machine learning-driven platform that turns a complex cardiac ultrasound into a complete, structured clinical report in less than two minutes, Hare is doing more than just saving doctors time. He is democratizing life-saving diagnostics, removing human error from the equation, and altering how the global medical community detects, tracks, and treats cardiovascular disease.
The Subjective Bottleneck of Cardiac Care
Cardiovascular disease remains the leading cause of death globally, claiming nearly twenty million lives each year. The primary tool used to diagnose and monitor these cardiac conditions is the echocardiogram. It is safe, non-invasive, and emits zero radiation. However, the true bottleneck of the system is not acquiring the image; it is reading it. An echocardiogram produces vast amounts of complex data, tracking blood flow velocities, valve movements, and chamber wall contractions across multiple views.
Traditionally, analyzing these images requires highly specialized training. A sonographer or cardiologist must manually select the best frames from a video file, use digital calipers to measure anatomical structures, and manually calculate metrics like the ejection fraction, which is the percentage of blood leaving the heart each time it contracts. Because the human eye interprets these moving boundaries differently, two world-class doctors can look at the same scan and arrive at significantly different measurements.
This variability introduces dangerous ambiguity into patient care. Furthermore, the sheer volume of manual work creates an administrative crisis. With studies taking up to forty-five minutes to manually measure and report, specialized echo labs face massive backlogs. In rural clinics, lower-income regions, or community hospitals that lack on-site imaging specialists, patients often wait weeks or months just to have their scans interpreted. This delayed access directly translates to delayed treatment, allowing conditions like heart failure or pulmonary hypertension to progress unchecked.
From E-Commerce Pioneer to MedTech Radical
To solve a deeply entrenched medical problem, it often takes an outsider with a fresh perspective on scale and automation. James Hare fits this profile perfectly. Before diving into clinical artificial intelligence, Hare built a highly successful career as a serial tech entrepreneur and executive. He holds a Bachelor of Arts from Harvard University and an MBA from Stanford University, focusing his early academic years on history and literature before pivoting into high-growth technology industries.
Hare’s early career includes foundational roles at internet pioneers like Netscape, where he managed international marketing during the dawn of the consumer web, and Ubisoft, where he directed marketing strategies during a period of rapid gaming infrastructure growth. His breakthrough as an entrepreneur came when he co-founded eDreams, an online travel agency that he grew into one of Europe’s largest e-commerce platforms and the largest publicly traded European travel company by profitability.
With over twenty years of experience scaling complex digital platforms, optimizing user experiences, and deploying machine learning algorithms in consumer software, Hare understood how to take massive, unstructured data sets and turn them into instantaneous, actionable user insights. However, moving from booking flights and marketing software to handling regulated medical software required a profound shift in intent and responsibility.
A Personal Wake Up Call
The transition from e-commerce to medicine was sparked by a deeply unsettling personal experience. Hare and his wife, Dr. Carolyn Lam, who is a world-renowned professor of cardiology at Duke NUS Graduate Medical School and a senior consultant at the National Heart Center Singapore, found themselves caught on the wrong side of medical ambiguity. Hare underwent a routine cardiac checkup and received two completely conflicting clinical reports regarding his own heart health based on manual echocardiogram readings. One report suggested a potential structural issue, while the other cleared him completely.
This emotional rollercoaster exposed a glaring systemic flaw to the couple. If a tech executive married to a leading global cardiologist could face terrifying diagnostic uncertainty due to manual measurement errors, what was happening to ordinary patients who lacked immediate access to top-tier medical expertise?
Dr. Lam understood the clinical limitations of manual tracing, while Hare recognized it as an automation deficit. They realized that the variation between the two reports was not a lack of medical knowledge, but an inherent limitation of human eyes trying to measure micro movements on a screen. Motivated by a desire to eliminate this terrifying ambiguity for families worldwide, they decided to combine forces. In 2017, alongside co-founder Dr. Yoran Hummel, an expert in echocardiography core labs, they incorporated the company in Singapore, initially naming it eko.ai before later rebranding to Us2.ai.
Building the Zero Click Clinical Engine
Building a medical AI company requires a fundamentally different playbook than building a consumer software startup. You cannot simply build fast and break things when human lives and strict regulatory frameworks are involved. Hare realized that for Us2.ai to gain traction among notoriously cautious healthcare institutions, the technology had to be seamless, objective, and integrated into existing workflows without adding extra friction.
Under Hare’s leadership, the company set out to develop a platform that achieved true zero-click automation. While existing medical software tools offered semi-automated features, which require a doctor to manually select a specific frame or click on the edges of a ventricle before the software calculates a number, Us2.ai aimed to automate the entire pipeline.
The resulting software connects directly to any existing ultrasound machine or picture archiving and communication system. Once a sonographer completes an ultrasound scan, the raw video files are uploaded to the platform. The AI automatically identifies the correct cardiac views, selects the ideal frames from the cardiac cycle, segments the chambers, traces the walls, and processes both 2D and Doppler data. Within seconds, it produces a complete, structured report containing comprehensive measurements, structural disease detection, and clear clinical findings.
To train an algorithm capable of matching and exceeding the precision of human specialists, Hare and his team tapped into massive, diverse global datasets. They partnered closely with Singapore’s Agency for Science, Technology and Research, leveraging scientists from the Bioinformatics Institute and the Institute of High Performance Computing. This scientific collaboration allowed them to train their deep learning models on millions of echocardiographic images representing varied patient demographics, ensuring the software’s accuracy remained robust regardless of age, gender, or ethnicity.
Navigating Regulation and Accelerating Growth
The true test for any medical technology platform lies in the clinical validation and regulatory clearance arenas. Under Hare’s operational guidance, Us2.ai pursued a rigorous, science-first validation strategy. Instead of relying purely on internal testing, the company submitted its software to intensive peer-reviewed scrutiny, resulting in landmark publications in top-tier medical journals including The Lancet Digital Health, Nature Communications, and Circulation.
A major turning point arrived when Us2.ai received its initial FDA clearance for its fully automated solution capable of measuring both 2D and Doppler cardiac ultrasound images. This was followed by a European regulatory mark, opening the doors to widespread international deployment. The company subsequently secured further FDA clearance for its expanded version, which introduced advanced strain imaging parameters to analyze the subtle deformation of the heart muscle.
More recently, the company achieved a breakthrough by securing FDA clearance for a deep learning model specifically designed to detect cardiac amyloidosis, which is a rare, notoriously under diagnosed condition where abnormal proteins build up in the heart tissue, often disguised as typical heart failure. By combining pattern recognition with guideline-based measurements, the software flags this deadly condition automatically during a standard ultrasound review.
This steady pipeline of regulatory success has driven robust commercial growth. The company raised an initial $ 4.5 million seed round led by Sequoia India, which is now Peak XV Partners, and EDBI, followed by a fifteen-million-dollar Series A round led by IHH Healthcare. These funds have allowed Hare to scale commercial operations globally, transitioning the company from a deep tech research project into a widely adopted clinical workflow tool used across continents.
Transforming the Global Landscape of Echocardiography
Today, Hare’s clinical vision is backed by concrete data from real-world hospital deployments. Independent clinical studies, including the prominent OPERA study presented at the European Society of Cardiology, have demonstrated that AI-assisted echocardiography is just as effective as the traditional expert standard, while completely eliminating interobserver variability.
The operational impact on healthcare systems is profound. The software slashes the time required to compile, analyze, and type a complete cardiac report down to less than two minutes. This significantly accelerates clinical workflows, allowing clinics to process higher daily scan volumes and drastically reduce patient waitlists. Furthermore, it delivers immediate bedside insights. Because the software generates structured data almost instantly, clinicians can review findings with patients before they even leave the exam room, accelerating the path to treatment.
By removing the reliance on a small circle of elite imaging specialists for basic measurements, the platform enables general practitioners, emergency room nurses, and technicians using portable, point-of-care ultrasound devices to access expert-level diagnostic insights anywhere.
The Startup Power of Strategic Alliances
Moving a lean startup into a deeply defensive global healthcare market requires an exceptionally clever commercial strategy. Hare’s core leadership philosophy is built around a clear principle, which is to minimize existential risk through world-class partnerships. Rather than trying to rebuild the medical ecosystem from scratch or deploy a massive direct sales force to thousands of individual hospitals, Hare has systematically aligned Us2.ai with the absolute titans of the pharmaceutical, software, and medical hardware industries.
In the pharmaceutical sector, Hare secured early, high-profile research collaborations with global giants like AstraZeneca, Janssen, and Roche. These pharmaceutical companies use Us2.ai’s automated software in massive, multi-site clinical drug trials. Because manual echocardiogram readings introduce too much human noise and variability into trial data, Us2.ai provides an objective, unvarying digital standard to measure how a new drug affects heart structure and function over time.
In the imaging and hardware sectors, Hare has pursued a powerful original equipment manufacturer and distribution strategy. The company finalized a major commercial integration with Fujifilm, embedding Us2.ai’s automated analysis capabilities directly into widespread clinical software environments. Similar distribution and platform partnerships with deepc, Harrison.ai, and Merative Merge ensure that Us2.ai’s software is instantly accessible to thousands of health systems worldwide through the imaging platforms they already use every day. By positioning his team to work directly with major industry gatekeepers, Hare has turned potential competitors into active distribution networks.
A Borderless Vision for Cardiac Equality
Looking toward the horizon, James Hare’s focus is on total democratization. The long-term goal for Us2.ai is to decouple top-tier cardiac diagnostics from geographical and financial privilege. As ultra-portable, handheld ultrasound probes become cheaper and more common, the only remaining barrier to universal cardiac screening is the specialized knowledge required to interpret the images. By putting an AI-driven digital expert inside every smartphone or tablet connected to an ultrasound probe, Us2.ai can bring reliable, affordable heart screenings to remote villages, community care centers, and developing economies that currently have zero access to echocardiography core labs.
For Hare, the journey from optimizing e-commerce transactions to automating heart health diagnostics is a reminder of what happens when proven software design principles are applied to deep human problems. By replacing slow, subjective manual measurement workflows with rapid, objective, and zero-click artificial intelligence, he is helping build a healthcare ecosystem where diagnostic error is minimized, clinical workflows are liberated, and expert-level cardiac insights are accessible to every single heartbeat on the planet.
