Harrison.ai vs Lunit (2026)
Two companies that overlap only on chest X-ray. Annalise.ai, a joint venture between an Australian technology firm and a large radiology provider, detects up to 124 findings on chest radiographs and up to 130 on noncontrast head CT, with a separately cleared triage portfolio. Lunit's center of gravity is breast cancer: INSIGHT MMG and INSIGHT DBT for mammography and tomosynthesis, with density, risk, quality and outreach products from the former Volpara business, and INSIGHT CXR Triage for chest X-ray in the US. Its strongest evidence is ScreenTrustCAD, a prospective Swedish screening study of 55,581 women. A buyer who needs comprehensive chest X-ray and head CT reading looks at Annalise. A breast screening program looks at Lunit.
- Comprehensive findings sets: up to 124 on chest X-ray and 130 on head CT, including neuro coverage Lunit does not offer.
- A defined US reimbursement path: Medicare new technology payment status, which changes the return calculation for a hospital.
- The first Breakthrough Device designation granted to a radiology triage device.
- Prospective screening evidence: in ScreenTrustCAD (The Lancet Digital Health, 2023), AI with one radiologist was noninferior to two radiologists across 55,581 women.
- A breast cancer platform: detection on mammography and tomosynthesis alongside density, risk, quality and patient outreach products.
- An outside comparison: a retrospective Swedish evaluation in JAMA Oncology (2020) compared three commercial algorithms, and Lunit's had the highest accuracy of the three.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Harrison.ai and Lunit are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Harrison.ai | Lunit |
|---|---|---|
| Primary category | Radiology & Imaging AI | Radiology & Imaging AI |
| Founded | 2019 | 2013 |
| Headquarters | Sydney, Australia | Seoul, South Korea |
| Website | harrison.ai | lunit.io |
Side by Side
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Each vendor in one paragraph
Written to be quoted whole. Each paragraph opens the AI Health Index profile of the vendor: what the product is, who buys it and what it does.
Radiology AI company headquartered in Sydney. Its radiology products were sold as Annalise.ai, including Annalise Enterprise CXR and Annalise Enterprise CTB, until Harrison.ai combined with Annalise.ai in February 2025 and renamed the Annalise.ai solutions Harrison.ai Radiology in October 2025; the annalise.ai domain now forwards to harrison.ai.
Source: AI Health Index, July 2026
Cancer focused medical AI company founded in 2013, headquartered in Seoul and listed on KOSDAQ. Its radiology line is Lunit INSIGHT: MMG for 2D mammography (FDA cleared 2021), DBT for tomosynthesis (cleared 2023) and CXR for chest X-ray (CXR Triage cleared 2021).
Source: AI Health Index, July 2026
Questions buyers ask
How do Harrison.ai and Lunit work with the EHR?
For Harrison.ai, the 510(k) summary for K222268 describes the software receiving DICOM chest X-ray studies from image and order management systems such as a PACS or RIS, running in parallel with the standard workflow, and returning a case level result to the PACS or RIS for worklist prioritization.
With Lunit, the company embeds its algorithms directly into imaging hardware through OEM relationships with major scanner manufacturers and distributes via major cloud infrastructure, meaning a customer can acquire the AI as part of equipment already being purchased rather than as a separate integration project. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified July 22, 2026. No vendor pays for placement.
How are Harrison.ai and Lunit priced and sold?
In Harrison.ai's case, the products are sold to healthcare organizations (public hospitals, private hospitals and private radiology providers) by contacting the company, and the site states they are not available for purchase by the general public.
Lunit sells INSIGHT and its breast platform direct and through imaging equipment and viewer partners, so the software can arrive inside or alongside a scanner or viewer purchase. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified July 22, 2026. No vendor pays for placement.
How do Harrison.ai and Lunit handle patient data?
With Harrison.ai, the company's privacy notice (last updated 20 November 2025), which covers its products and services as well as its websites, states that it does not use any content uploaded into its services, including demos, product trials and evaluations, for model training.
In Lunit's case, the INSIGHT MMG FAQ says images from commercial sites are retained only for the duration of processing and are not used for retraining, that the models do not learn in real time, and that training data is biopsy proven material sourced through formal collaboration agreements. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified July 22, 2026. No vendor pays for placement.
What evidence is published for Harrison.ai and Lunit?
For Harrison.ai, the comprehensive chest X-ray model is the subject of a retrospective multireader multicase study of radiologist accuracy with and without the model, published in The Lancet Digital Health in 2021. The company has reported a 32 percent improvement in head CT diagnostic accuracy averaged across findings, without the comparator or design alongside it.
An independent external evaluation in JAMA Oncology (Salim and colleagues, 2020) compared three commercial algorithms on a retrospective Swedish screening cohort, and Lunit's had the highest accuracy. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified July 22, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Clinical Decision Support page.
Annalise.ai's record has not yet been reviewed on this site, so its side of this page rests on the build record. Its reported 32 percent head CT accuracy improvement has no published study detail.
Lunit's US mammography clearance is for an adjunct viewed after the radiologist's initial read, and its evidence frames AI with one radiologist as a replacement for double reading, so a double reading program should treat the staffing change as the real decision. Lunit publishes no business associate position for its products, and a US buyer should settle those terms with either company. Neither publishes pricing.