Lunit vs Viz.ai (2026)
Two imaging AI companies operating on completely different clocks. Lunit works cancer detection across chest radiograph and mammography, where the failure is a missed lesion discovered months later and the evidence that matters comes from screening populations. Viz.ai works acute triage and notification, holding the first ever authorization in that category, where the failure is a delayed intervention measured in minutes and the product's real work is mobilising the treating team. Neither competes with the other, and a health system may well run both in different departments. What the pair shows is that imaging AI evidence is not interchangeable: a screening product must be judged on positive predictive value at your prevalence, and an acute product on time to treatment.
- Cancer imaging is the focus across chest radiograph and mammography, with a listed parent and regulatory footprints in multiple markets.
- The evidence base in screening populations is deeper than for most detection vendors, which is the setting where sensitivity and specificity both bite.
- For a screening programme, a vendor whose portfolio is built around cancer detection is a closer fit than an acute triage platform.
- Its stroke product holds the first ever authorization for computer aided triage and notification, and the platform mobilises the treating team rather than only flagging.
- The evidence measures care delivery rather than detection accuracy, which is the harder result and the one tied to patient benefit.
- For a time critical pathway the constraint is coordination rather than interpretation.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Lunit and Viz.ai 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
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 Lunit its top capability grade on several axes, including AI Centrality, Model and Technology Transparency and Clinical and Operational Evidence. Set against Viz.ai, Lunit grades higher on Model and Technology Transparency, AI Governance and Bias Disclosure and AI Liability and Recourse. 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
The AI Health Index awards Viz.ai its top capability grade on several axes, including AI Centrality, Autonomy and Oversight Model and Clinical and Operational Evidence. Set against Lunit, Viz.ai grades higher on Autonomy and Oversight Model and Setting and Specialty Coverage. 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 Lunit or Viz.ai?
On the axes where the AI Health Index separates them, Lunit grades higher on Model and Technology Transparency, AI Governance and Bias Disclosure and AI Liability and Recourse, and Viz.ai grades higher on Autonomy and Oversight Model and Setting and Specialty Coverage. 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 Lunit and Viz.ai differ most?
The widest separation the AI Health Index records between Lunit and Viz.ai is on Model and Technology Transparency, where Lunit grades A and Viz.ai grades B. 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 Lunit and Viz.ai grade the same?
The AI Health Index grades Lunit and Viz.ai the same on several axes, including AI Centrality, Model Supply Chain Disclosure and Clinical and Operational Evidence. 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 Lunit and Viz.ai not disclosed?
At the last review, at least one of Lunit and Viz.ai published thin or absent detail on Model Supply Chain Disclosure. 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.
These operate on different clocks and the comparison is about which problem you have: cancer screening plays out over months and its failure is a missed lesion, while acute triage plays out over minutes and its failure is a delayed intervention. Viz.ai publishes no independent security attestation and no business associate terms.
Neither publishes subgroup performance, and in screening that gap is consequential because prevalence and presentation both vary by population, which changes positive predictive value more than sensitivity does.