Harrison.ai company profile: valuation, funding & revenue

This Harrison.ai company profile covers the company's valuation, revenue, funding rounds, investors and history. Harrison.ai works in healthcare, with a focus on AI for radiology and pathology. It was founded in 2018 and is headquartered in Sydney, New South Wales, Australia. Its latest valuation on record is About AU$789 million (February 2025). Every figure links to a public source, and anything the company hasn't disclosed is marked as such.

Revenue

Funding history

Harrison.ai timeline

Key dates from the sources on this page, oldest first. Metric snapshots are listed after the funding events.

• 2018 — Harrison.ai is founded in Sydney by Aengus Tran (CEO) and Dimitry Tran.
• Feb 2025 — Series C: US$112M (AU$179M), valuing the company at About AU$789M (disclosed later). Investors: Aware Super, ECP and Horizons Ventures (co-leads); National Reconstruction Fund.

Investors

Overview

Harrison.ai develops artificial intelligence that helps doctors read medical images. Its flagship product, sold under the Annalise brand, analyses chest X-rays, brain CT scans and other images, flagging dozens to more than a hundred possible findings, from collapsed lungs and fractures to bleeding in the brain, so radiologists can work faster and miss fewer problems. Harrison.ai has also built a radiology foundation model, Harrison.rad.1, and is expanding into pathology. It's one of Australia's most prominent health technology companies and has a growing presence in the UK, Europe, Asia and the United States.

Brothers Aengus Tran, the CEO, and Dimitry Tran founded Harrison.ai in Sydney in 2018. Aengus is a medical doctor who studied at the University of Sydney; Dimitry has a background in engineering and business. Their goal was to apply AI to scale the capacity of healthcare systems facing shortages of specialists and rising demand for imaging.

Products

• Annalise Enterprise CXR: analyses chest X-rays for more than a hundred findings.
• Annalise Enterprise CTB: analyses non-contrast brain CT scans, including urgent findings such as haemorrhage.
• Triage tools: prioritise urgent cases in radiologists' worklists so the most critical patients are seen first.
• Harrison.rad.1: a radiology-specific foundation model that can interpret images and answer questions about them, offered to researchers and partners.
• Pathology: AI tools developed through its Franklin.ai joint venture with Sonic Healthcare.

Regulatory approvals and adoption

Harrison.ai's products have received regulatory clearances in many markets, including multiple US FDA 510(k) clearances, CE marking in Europe and approvals in the UK, Australia and Asia. Its tools are used by hospitals and radiology groups in many countries, including NHS trusts in the UK, where AI chest X-ray tools have been deployed to help reduce backlogs. Its early partner I-MED, one of Australia's largest radiology providers, helped develop and test the technology on large volumes of real-world scans.

Funding

Harrison.ai's early investors include Horizons Ventures, the fund of Hong Kong billionaire Li Ka-shing, Blackbird and Skip Capital. In February 2025 it raised a US$112 million (AU$179 million) Series C co-led by Aware Super, ECP and Horizons Ventures, with Australia's National Reconstruction Fund Corporation making its first investment, an AU$32 million equity stake. The company didn't disclose a valuation at the time; its founders later told Forbes Australia that the round was at a valuation of about AU$789 million. Harrison.ai has said it will use the funds to expand in the US and develop new products. It also restructured in 2025, cutting about 15% of staff, while reporting strong revenue growth.

Competition

Harrison.ai competes with radiology AI companies such as Aidoc, Lunit, Qure.ai, Gleamer and Annalise's many smaller rivals, and with imaging equipment makers like GE HealthCare, Siemens Healthineers and Philips, which add AI to their systems. Large AI labs are also building general medical models. Harrison.ai's advantages are its comprehensive coverage of findings in a single product, regulatory clearances and clinical validation.

Harrison.ai at a glance

Harrison.ai is a Sydney medical AI company founded in 2018 by brothers Aengus and Dimitry Tran. Its Annalise products analyse chest X-rays and brain CT scans, and it has built the Harrison.rad.1 radiology foundation model. It raised a US$112 million Series C in February 2025, co-led by Aware Super, ECP and Horizons Ventures, at a valuation the founders later put at about AU$789 million.

Why radiology needs AI

Demand for medical imaging has grown far faster than the number of radiologists in many countries. Ageing populations, more use of scans in diagnosis and backlogs from the pandemic mean radiologists face huge workloads, and delays in reporting can harm patients. AI tools can help by detecting findings automatically, prioritising urgent cases and reducing missed abnormalities. Studies of comprehensive chest X-ray AI have shown improved accuracy when radiologists use it, although results vary by setting. Our guide to healthcare AI startups covers the wider market.

Comprehensive versus single-finding AI

Many early radiology AI products detected a single condition, such as lung nodules or stroke. Hospitals found it hard to buy and integrate dozens of separate tools. Harrison.ai took a different approach, building models that detect a broad range of findings in one product, closer to how a radiologist reads a scan. This comprehensive approach is harder to develop and gain approval for, but more useful in practice, and has become a key part of its sales pitch.

Business model and reimbursement

Harrison.ai typically licenses its software to hospitals and radiology providers, priced per scan or by subscription. A major challenge for radiology AI companies is reimbursement: in many countries, insurers and health systems don't pay extra for AI analysis, so providers must justify costs through productivity and quality gains. Changes to reimbursement rules, particularly in the US, could significantly expand the market.

Questions for hospitals

• Which findings and scan types does the product cover, and with what clearances in your country?
• How has it performed in validation studies on populations like yours?
• How does it integrate with your PACS and reporting systems?

How radiology AI is validated

Before AI can be used on patients, it must show that it performs accurately across different populations, scanners and hospitals. Developers test models on large sets of scans labelled by expert radiologists, measure how often they correctly identify or miss findings, and run studies comparing radiologists' accuracy with and without AI. Regulators review this evidence before granting clearance. After deployment, hospitals monitor performance, because changes in equipment or patient populations can affect results. Harrison.ai trained its models on millions of labelled images and has published studies in peer-reviewed journals, which has helped it gain credibility with clinicians and regulators.

Timeline

• 2018: Aengus and Dimitry Tran found Harrison.ai in Sydney.
• 2020–2021: Annalise chest X-ray and brain CT products launch and gain approvals in Australia, Europe and the UK.
• 2022–2024: multiple US FDA clearances; expansion across hospitals and radiology groups in several countries.
• 2024: launches the Harrison.rad.1 radiology foundation model.
• February 2025: raises a US$112 million Series C co-led by Aware Super, ECP and Horizons Ventures.

Latest developments (October 2026)

Our October 2026 review found no new round for Harrison.ai after its February 2025 Series C of A$179 million (about US$112 million), co-led by Aware Super, ECP and Horizons Ventures, according to BioWorld. The Sydney company has been using that capital to expand its radiology and pathology AI into the US, UK and Asia.

What to watch

Watch US expansion and FDA clearances, adoption of Harrison.rad.1, pathology progress, any new funding and whether it becomes Australia's next health technology unicorn.

Takeaways

Radiology departments can use AI to prioritise urgent scans and reduce missed findings. Founders can learn from Harrison.ai's clinician-led approach. Investors should watch reimbursement developments, which shape the size of the market.

Sources

Every figure on this page comes from the public sources below. Where sources disagreed, we used the company's own announcement or a primary news report. Private-company data changes; check the date beside each figure.

1. Forbes Australia
2. TechCrunch