Infervision vs Lunit (2026)
Two Asian origin imaging AI companies that both reached international markets, with different centres of gravity. Lunit is cancer focused across chest radiograph and mammography, publicly listed, with the deeper evidence base in screening populations, which is the setting where a false positive rate multiplies across a large healthy denominator. Infervision spans lung nodule detection and chest interpretation across modalities with United States operations alongside its origin market, which gives an American buyer a closer support relationship. For a screening programme, Lunit's evidence is the more relevant. For a health system wanting breadth across the imaging estate from one vendor, Infervision reaches further. Ask both for performance at your prevalence rather than in their validation cohorts.
- Cancer detection across chest radiograph and mammography with a listed parent and regulatory footprints in multiple markets.
- The evidence base in screening populations is deeper than most detection vendors, which is where both sensitivity and specificity bite.
- For a screening programme, a portfolio built around cancer detection is a closer fit than general findings reading.
- Its suite spans lung nodule detection and chest interpretation with United States operations alongside its origin market.
- Coverage extends across modalities rather than radiography alone, so one vendor reaches more of the imaging estate.
- For a buyer wanting an established American support relationship from a non Western vendor, that presence matters.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Infervision 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 | Infervision | Lunit |
|---|---|---|
| Primary category | Radiology & Imaging AI | Radiology & Imaging AI |
| Founded | 2015 | 2013 |
| Headquarters | Beijing, China | Seoul, South Korea |
| Website | global.infervision.com | lunit.io |
Side by Side
Each record in one paragraph
Written to be quoted whole. Each paragraph states what the AI Health Index verified about the vendor, with the caveats attached. Generated from this pair’s live capability grades, so it moves when a grade moves.
The AI Health Index awards Infervision its top capability grade on AI Centrality, FDA and Regulatory Status and Setting and Specialty Coverage. Set against Lunit, Infervision grades higher on Setting and Specialty Coverage. Its thinnest published disclosure sits on Model Supply Chain Disclosure and AI Liability and Recourse. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.
Source: AI Health Index, August 2026
The AI Health Index awards Lunit its top capability grade on several axes, including AI Centrality, Model and Technology Transparency and Clinical and Operational Evidence. Set against Infervision, Lunit grades higher on several axes, including Model and Technology Transparency, Clinical and Operational Evidence and AI Governance and Bias Disclosure. Its thinnest published disclosure sits on Model Supply Chain Disclosure. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.
Source: AI Health Index, August 2026
Questions buyers ask
Should we choose Infervision or Lunit?
On the axes where the AI Health Index separates them, Infervision grades higher on Setting and Specialty Coverage, and Lunit grades higher on several axes, including Model and Technology Transparency, Clinical and Operational Evidence and AI Governance and Bias Disclosure. Lunit leads on the greater share of scored axes, but the split means the decision turns on which constraint is binding rather than on an overall winner.
Where do Infervision and Lunit differ most?
The widest separation the AI Health Index records between Infervision and Lunit is on Model and Technology Transparency, where Infervision grades C and Lunit grades A. That axis sits in the AI Capability group, so it should carry the most weight for a buyer whose binding constraint is how much of the work the model itself is trusted to do.
Where do Infervision and Lunit grade the same?
The AI Health Index grades Infervision and Lunit the same on several axes, including AI Centrality, Autonomy and Oversight Model and Model Supply Chain Disclosure. Neither holds an advantage the index can evidence on those axes, so they should not carry weight in a selection between these two.
What have Infervision and Lunit not disclosed?
At the last review, at least one of Infervision and Lunit published thin or absent detail on Model Supply Chain Disclosure and AI Liability and Recourse. The AI Health Index treats an absent disclosure as a gap in the public record rather than a failure of the product, so these are the axes to get in writing during diligence instead of inferring from the grade.
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.
Both are non Western origin imaging vendors and the pattern this index records applies to both: regulatory effort follows market access while commercial assurance documentation is thinner, so ask for attestations and business associate terms explicitly. Findings counts are not comparable between vendors because each counts differently.
Prevalence in your own population determines the false positive burden more than published sensitivity does, and neither publishes performance stratified that way, which matters most in screening where the denominator is large and healthy.