Annalise.ai vs Lunit (2026)
Both are FDA cleared, AI centrality A detection vendors on chest X-ray, but their scopes barely overlap, so for most buyers the choice follows the clinical need. If you need comprehensive multi finding coverage including head CT and a defined Medicare reimbursement path, start with Annalise.ai, whose breadth and neuro coverage Lunit does not match. If your priority is cancer detection backed by the deepest, most independently validated evidence in imaging AI, start with Lunit, the only vendor here that has twice submitted to third party head to head benchmarking. Annalise reads up to 124 findings on chest X-ray and 130 on head CT. Lunit is cancer focused across chest X-ray and mammography, with more than 100 peer reviewed publications behind it.
- Comprehensive multi finding breadth including neuro: up to 124 findings on chest X-ray and 130 on head CT, where Lunit is confined to cancer detection on chest X-ray and mammography with no head CT coverage.
- A defined US reimbursement path: Medicare New Technology Add on Payment status, which changes the return calculation for a hospital buyer.
- Time critical triage strength: the highest number of cleared triage findings on chest X-ray plus the first Breakthrough Device Designation ever granted to a radiology triage device.
- The deepest and most independent evidence base of any imaging vendor in the index: more than 100 peer reviewed publications, and the only one here to submit to third party head to head benchmarking twice, in JAMA Oncology against two commercial mammography products and in a Radboud multi vendor lung nodule validation.
- Cancer depth across two modalities: chest X-ray for lung plus mammography and tomosynthesis for breast, with published work specifically on dense breast tissue performance, the best documented failure mode in mammography screening.
- A lower friction adoption path: algorithms embedded directly into scanner hardware through OEM relationships, so a buyer can acquire the AI as part of equipment already being purchased.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Annalise.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 | Annalise.ai | Lunit |
|---|---|---|
| Primary category | Radiology & Imaging AI | Radiology & Imaging AI |
| Founded | 2019 | 2013 |
| Headquarters | Sydney, Australia | Seoul, South Korea |
| Website | annalise.ai | 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 Annalise.ai its top capability grade on AI Centrality, FDA and Regulatory Status and Setting and Specialty Coverage. Set against Lunit, Annalise.ai grades higher on Model Supply Chain Disclosure, Deployment Model and Data Residency and Setting and Specialty Coverage. 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, July 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 Annalise.ai, 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, July 2026
Questions buyers ask
Should we choose Annalise.ai or Lunit?
On the axes where the AI Health Index separates them, Annalise.ai grades higher on Model Supply Chain Disclosure, Deployment Model and Data Residency and 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 Annalise.ai and Lunit differ most?
The widest separation the AI Health Index records between Annalise.ai and Lunit is on Model Supply Chain Disclosure, where Annalise.ai grades C and Lunit grades D. 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 Annalise.ai and Lunit grade the same?
The AI Health Index grades Annalise.ai and Lunit the same on several axes, including AI Centrality, Autonomy and Oversight Model and AI Safety and PHI Stewardship. 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 Annalise.ai and Lunit not disclosed?
At the last review, at least one of Annalise.ai and Lunit 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.
Both are FDA cleared, AI centrality A detection vendors deployed across more than 40 countries, and neither publishes a security attestation or data residency terms. Their scopes barely overlap beyond chest X-ray: Lunit is cancer focused with no neuro, musculoskeletal, or emergency coverage, while Annalise is comprehensive findings with no mammography, so for most buyers the choice follows the clinical need rather than a like for like comparison.
Annalise's evidence leans on deployment scale rather than peer reviewed outcomes, and its headline 32 percent head CT accuracy improvement lacks published study detail. Both are headquartered outside the US, Lunit in Korea and Annalise as an Australian joint venture, so a US buyer should establish business associate terms. Lunit's own evidence frames AI plus one radiologist as a replacement for two reader double reading, so buyers in double reading programs should treat the staffing implication as the real decision.