Aengus Tran traded medical practice to build AI software that delivers quick and accurate diagnoses of X-rays and scans. Now, the 32-year-old CEO of Sydney-based Harrison.ai and a 30 Under 30 Asia alum is targeting America\u2019s overstretched healthcare system.<\/p>\n
While studying medicine in Sydney in 2015 with a view to specializing in cardiology, Aengus Tran did a two-month clinical placement in his native Vietnam that upended his plan. At the Tam Duc Cardiology Hospital in Ho Chi Minh City, the doctor-to-be witnessed first-hand how the short-staffed hospital struggled to provide timely diagnoses to its patients. For Tran, it was a moment of clarity that medicine \u201cneeds a system-wide change, one based on technology that can read scans and make diagnoses instantly\u2026and is run so effectively and efficiently that it is available to everyone,\u201d he says.<\/p>\n
With a mission to drive that change, he cofounded Harrison.ai, a clinical AI service provider, in 2018 in his final year of medical school with his older brother, Dimitry, then-head of innovation at Australian private hospital giant Ramsay Health Care. Using the country\u2019s mature healthcare market as a testing ground, the pair developed AI software capable of analyzing chest X-rays and chest and brain CT scans, flagging critical cases and generating draft reports. The company says its software can cut diagnostic report turnaround times by up to 40% in time-critical cases and boost overall reporting speeds by 10%. <\/p>\n
As of May, Harrison.ai\u2019s software was being used by more than 3,400 clinicians in over 1,000 hospitals and clinics in more than 40 countries. Its two biggest markets are Australia, where it says it serves half the country\u2019s roughly 3,200 registered radiologists, and the U.K., where it assesses more than 40% of all chest X-rays for NHS England, part of the U.K.\u2019s National Health Service. It also has a presence across Asia and in Europe. <\/p>\n
Now Tran, 32, is targeting expansion in what he believes could become Harrison.ai\u2019s biggest market, the U.S. \u201cWe\u2019ve already built a very comprehensive AI that makes 455 different diagnoses and has been battle-tested,\u201d says the 30 Under 30 Asia alum from 2020<\/a>. \u201cThe U.S. is our next corridor.\u201d <\/p>\n The startup\u2019s $112 million Series C funding round<\/a> in February last year at an undisclosed valuation brought its total amount raised to more than $240 million and will be used to bankroll the expansion. Investors in that round included pension fund Aware Super and fund manager ECP Asset Management, both Australian, and Hong Kong\u2019s Horizons Ventures, a VC firm cofounded by billionaire Solina Chau<\/a> and backed by the territory\u2019s richest man, Li Ka-shing<\/a>.<\/p>\n In May, Harrison.ai received another big-name backer when Hong Kong-based conglomerate Jardine Matheson, controlled by the billionaire Keswick family<\/a>, agreed to acquire I-Med Radiology Network, which holds a minority stake in Harrison.ai, in a deal that puts I-Med\u2019s enterprise value at $2.4 billion. The Australian diagnostic imaging provider, the country\u2019s largest by number of clinics, bought its Harrison.ai stake in 2021.<\/p>\n Harrison.ai generates revenue from the annual subscription fee paid by healthcare providers to access its platform, which is based on the expected volume of scans. When a subscribing radiologist opens an X-ray or CT scan using their usual software, Harrison.ai\u2019s findings appear as an overlay that also prioritizes urgent cases.<\/p>\n Track RecordSo far, Harrison.ai has raised more than $240 million* from VC heavyweights, including billionaire Solina Chau\u2019s Horizons Ventures. <\/p>\n *Excluding angel investors and grants<\/p>\n Source: Harrison.ai, Crunchbase<\/p>\n In the year ended June 30, 2025, revenue from customer contracts jumped 54% from a year earlier to A$7.3 million ($5.1 million), according to a filing made by Harrison.ai to the Australian Securities and Investments Commission. It swung to a net loss of A$118 million in the same period from a year-earlier net profit of A$4.4 million. The company says the filing only provides \u201ca partial picture\u201d of its operations and declines to comment on the reason for the loss. <\/p>\n Unfazed, Tran is forging ahead in what he believes is a burgeoning market. The shortage of radiologists he witnessed in Vietnam is a universal problem as aging populations put a strain on healthcare systems across the world. In the U.S., there are about 11 radiologists per 100,000 people, according to the American College of Radiology, while the Medical Board of Australia says the country has roughly 12 for every 100,000 people. In the U.K., meanwhile, a 31% shortfall of clinical radiologists results in long waiting times for patients, according to the Royal College of Radiologists. <\/p>\n The shortage is just one factor driving demand for clinical AI services. San Francisco-based Grand View Research cites the increasing need for early and accurate diagnosis amid the mounting volume of imaging data being generated. The firm expects the industry to notch up a compound annual growth rate (CAGR) of 35% between 2026 and 2033 to top $20 billion, led by the U.S., which accounts for almost half the market and where 600 million medical imaging procedures are conducted yearly, according to Dublin-based Research and Markets. <\/p>\n The country is already Harrison.ai\u2019s third-largest revenue contributor, but Tran is aiming to make it the biggest by next year. Harrison.ai entered the U.S. in 2022, with Dimitry relocating to Cambridge, Massachusetts, to oversee the expansion as managing director, Americas. Since then, it has landed some key clients, including the Mass General Brigham healthcare system in Boston; Radiology Associates of North Texas, one of the nation\u2019s largest private radiology practices based on number of radiologists; and Inland Imaging, a medical imaging provider headquartered in Washington state.<\/p>\n \u201cOther companies built AI that detects A, B or C while we have the A-to-Z detection system.\u201d\n<\/p>\n But Harrison.ai is up against hefty competition, including Israel\u2019s Aidoc and India\u2019s Qure.ai. The former was set up in 2016 and has raised a total of $500 million from blue-chip American VC firms such as Nvidia\u2019s NVentures and General Catalyst. It specializes in the diagnosis of X-rays and CT scans for life-threatening conditions such as strokes and hemorrhages and its software is also geared to provide clinicians with services such as mobile alerts about critical cases and a chat function between hospital departments.<\/p>\n Qure.ai, also founded in 2016, has raised a total of $126 million from investors including U.S. pharma giant Merck\u2019s venture fund, and Novo Holdings, the controlling shareholder of Danish drugmaker Novo Nordisk. The company is best-known for assessing X-rays for tuberculosis and lung cancer detection, and its software notifies clinicians when a patient needs a follow-up scan.<\/p>\n Asked about his competitors, Tran says Harrison.ai\u2019s edge is the larger number of findings it is capable of analyzing. Its chest X-ray tool can identify up to 124 findings within 20 seconds, and that has led to a 45% increase in diagnostic accuracy, according to the company. Its CT brain software can detect as many as 130 in less than two minutes while its CT chest software can spot over 200. By comparison, Aidoc is trained to detect about 30 acute findings while Qure.ai is capable of roughly 100.<\/p>\n \u201cIf you think of AI as a spell checker for radiologists, preventing them from missing critical things, other companies built AI that detects A, B or C while we have the A-to-Z detection system,\u201d Tran says. Rhidian Bramley, a consultant radiologist at the Christie NHS Foundation Trust in Manchester, says Harrison.ai\u2019s chest X-ray software has boosted its lung cancer detection rates and accelerated the process, with 90% of chest X-rays of suspected cases being reported the same day, up from 20% earlier. \u201cHarrison is the leader in terms of the number of findings in its chest X-ray solution,\u201d he says.<\/p>\n Scanning The FieldAs it expands in the U.S. market, Harrison.ai is up against competitors such as Israel\u2019s Aidoc and India\u2019s Qure.ai. <\/p>\n Sources: Harrison.ai, Aidoc, Qure.ai<\/p>\n That said, the U.S. market is a challenge as it is among the most stringent for clinical AI companies, which are required to secure approval from the U.S. Food & Drug Administration for each discrete finding their software is capable of identifying. As Prashant Warier, cofounder and CEO of Qure.ai says, \u201cHaving a lot of findings that you can detect on a scan is an algorithmic capability, but to have a product that is FDA cleared, it takes a lot of time.\u201d <\/p>\n Qure.ai and Aidoc each have roughly twice as many findings approved by the FDA as Harrison.ai. However, Warier says it\u2019s not a winner-takes-all market. \u201cIf you look at AI in radiology, there are probably thousands, if not hundreds of thousands, of problems, and everybody is solving their own piece,\u201d he says. <\/p>\n To better compete, Harrison.ai in November started to include third-party tools on its platform such as those of Singapore\u2019s Us2.ai, which specializes in cardiac ultrasounds, and South Korea\u2019s Lunit for cancer diagnostics. Harrison.ai doesn\u2019t charge a markup or commission for these third-party offerings because, as Tran explains, \u201cTo us, the benefit is we have a wider portfolio of offerings for customers.\u201d<\/p>\n The company is also moving beyond \u201cdecision support and detection into radiologist reasoning,\u201d says Tran, with new foundational models that parse X-rays like a human radiologist, taking into account the patient\u2019s clinical history. Called Harrison.rad and using a chatbot interface, the model is still in the testing phase and presently available only to researchers and select customers. \u201cWe don\u2019t want to just release it into the wild. We want to do it in a responsible and thoughtful way,\u201d Tran notes.<\/p>\n Aidoc also has third parties on its platform and offers a reasoning engine that provides multiple findings simultaneously and prioritizes critical cases. Its chief business officer, Tom Valent, says Aidoc sets itself apart by acting like an operating system that brings \u201cimaging AI, clinical workflows, and enterprise analytics into a single coherent platform.\u201d<\/p>\n But Chris Liu, investor at Horizons Ventures, insists Harrison.ai\u2019s extensive offering is a key differentiator. Companies developing AI tools that only flag specific diseases limit workflow automation because physicians still have to review every scan to rule out other conditions, Liu says. Harrison.ai, he adds, is positioned to become \u201cthe standard of care for early detection diagnostics\u201d in the next five years.<\/p>\n \u201cNo one else offers anything near the level of comprehensiveness that Harrison.ai provides,\u201d concurs Samantha Wong, a partner at Australian VC firm Blackbird Ventures, an early investor. \u201cThe Tran brothers, one a medical doctor and AI engineer, the other a healthcare executive\u2026had the right mix of skills to do exactly what was needed.\u201d<\/p>\n Harrison.ai\u2019s chest X-ray tool shows findings as an overlay.<\/p>\n Harrison.ai<\/p>\n Tran and his brother were born in Vietnam to two high school math teachers. Growing up with a programming-enthusiast father, Tran learned coding early. He moved to Australia at age 16 for high school, joining Dimitry, who was already working in Sydney. It was a massive culture shock, he recalls, and although he had learned English at school in Vietnam he found the Australian accent challenging. Pushing himself to make friends beyond the Vietnamese community helped him to assimilate, he says.<\/p>\n While Trans says he is \u201ca programmer at heart,\u201d when it came to his career he chose to study medicine at the University of New South Wales. Following his placement in Vietnam, he started looking for ways to combine his two interests. While attending a talk by an executive from Virtus Health, one of Australia\u2019s biggest assisted reproductive service providers, he learnt how difficult it was to select the most viable fertilized egg for implantation.<\/p>\n That sparked a business idea and he created Ivy, an AI tool in collaboration with Virtus that analyzes videos of embryos in test tubes to identify the one most likely to result in pregnancy. Ivy has increased the rate of successful implantation to 93% from 65% when human embryologists make the selection, according to the Australian Alliance for Artificial Intelligence in Healthcare, a network of specialists. \u201cThat was the very first time I glimpsed the vision of what would become Harrison.ai,\u201d recalls Tran who sees his entrepreneurial efforts as \u201ca different way of practicing medicine.\u201d<\/p>\n In 2019, Virtus sold the rights to Ivy\u2019s technology to Swedish IVF firm Vitrolife for an initial payment of $6 million with an additional $2 million to be paid based on product-development targets over a three-year period. The same year, Tran raised $20 million for Harrison.ai in a Series A funding round that included Horizons Ventures and Ramsay Health Care, Dimitry\u2019s former employer. <\/p>\n \u201cThe Tran brothers, one a medical doctor and AI engineer, the other a healthcare executive\u2026had the right mix of skills to do exactly what was needed.\u201d\n<\/p>\n At first, the brothers focused on creating just a few diagnostic tools, but soon realized it would be more lucrative to offer a broader array. To speed things along, they formed a joint venture in late 2019 with I-Med to set up the first software platform, Annalise.ai. This helped address one of the biggest challenges facing AI diagnostic startups: access to a large set of scans required to train AI models. <\/p>\n Tran also bought data from third-party providers, whom he declines to name, and went on to gain access to a vast multiethnic dataset in 2023 when NHS England signed on as a client. An Asian dataset became available the same year when Harrison.ai was incorporated in all emergency rooms at Hong Kong\u2019s public hospitals.<\/p>\n But the founders soon encountered an issue that looms over AI diagnostic firms hungry for data to train their models: patient data protection. The scans provided by I-Med to Annalise.ai had been stripped of all obvious personal identifiers, but in 2024 a local media report accused I-Med of providing images without patient consent to Annalise.ai between 2020 and 2022. The Office of the Australian Information Commissioner began inquiries with a view to opening an investigation but last August said it was satisfied the scans had been adequately de-identified and I-Med had not breached Australia\u2019s Privacy Act.<\/p>\n Harrison.ai bought the shares it didn\u2019t already own in Annalise.ai from I-Med in 2024 and has been gradually rebranding the platform Harrison.ai Radiology. Asked about the controversy, Tran says: \u201cWe deeply believe in doing the right thing by the patient, including treating the datasets that we use with utmost care and respect, and meeting all the laws and regulations.\u201d<\/p>\n Elsewhere, Tran says one of his biggest challenges has been figuring out how to lead a rapidly growing startup that went from just himself as the sole programmer and Dimitry managing business operations to about 200 employees now. To develop Harrison.ai into a global healthcare system, he knew he had to build \u201ca diverse, multidisciplinary team\u201d to tackle everything from data engineering to distribution and regulatory clearances. His experience of adjusting to life in Australia as a teenager has helped him manage Harrison.ai\u2019s global staff, he discloses.<\/p>\n \u201cSometimes people ask if I gave up on medicine,\u201d Tran says. \u201cI did not. All the things I learned in medicine and all the experience I had, I apply every day.\u201d <\/p>\n Check out our full Forbes 30 Under 30 Asia 2026 list here<\/a>.<\/a><\/p>\n 30 UNDER 30 ASIA RELATED ARTICLESForbesMeet The Forbes 30 Under 30 Asia Class Of 2026By Rana Wehbe Watson<\/a>Forbes30 Under 30 Asia 2026: Meet The Entrepreneurs Building AI For Individuals And EnterprisesBy Yue Wang<\/a>Forbes30 Under 30 Asia: The Healthtech Founders And Researchers Pushing Boundaries Of Scientific DiscoveryBy Yue Wang<\/a>ForbesForbes 30 Under 30 Asia: The Social Entrepreneurs Tackling Issues From Food Waste To InequalityBy Zinnia Lee<\/a>ForbesMeet The Forbes 30 Under 30 Asia Class Of 2025By Rana Wehbe Watson<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"Aengus Tran traded medical practice to build AI software that delivers quick and accurate diagnoses of X-rays and…\n","protected":false},"author":2,"featured_media":704027,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[185489,342655,256,254,255,64,63,272203,95529,342654,45431,105,20375],"class_list":["post-704026","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-30-under-30","tag-aengus-tran","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-au","tag-australia","tag-clinical-ai","tag-ct-scan","tag-harrison-ai","tag-healthcare-ai","tag-technology","tag-x-ray"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/704026","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=704026"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/704026\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/704027"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=704026"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=704026"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=704026"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}