← All Categories

Digital Pathology AI

The pathology AI companies and vendors applying machine learning to tissue, cell, and slide based diagnosis: whole slide image analysis, cell classification and counting, and prognostic or predictive models derived from pathology images. The category is distinct from radiology imaging in what it analyzes and in how it is regulated, and regulatory status is the first thing a buyer should establish rather than the last. Many products sold and used in the United States today are labeled Research Use Only, meaning they may not be used for clinical diagnostic purposes even where the same product carries a CE mark in Europe and even where the vendor is generating revenue. Research Use Only is not a stage of development, it is a permitted use restriction, and a platform being commercially available says nothing about whether its outputs may inform a diagnosis. Buyers should also separate the workflow layer from the algorithms, since several vendors operate open platforms hosting third party models with differing regulatory status on the same screen, and should confirm whether detection thresholds are vendor fixed or customer configurable, because a tunable sensitivity threshold moves part of the clinical risk decision onto the laboratory.

The short answer

The AI Health Index grades 37 digital pathology AI vendors inside a graded population of 670, covering the models that read a whole slide image and return a diagnostic, prognostic or biomarker finding, along with the image management layer they run on. The grades carry an uncomfortable pattern for this category: the axis that should matter most to a pathology buyer is the one the field grades worst on. Setting and Specialty Coverage sits at 2 of 37 on an A, and stain, scanner and preparation differences are precisely what determine whether a model trained somewhere else will work in your laboratory.

Buyer guide

Best medical imaging AI →

This category graded alongside radiology and imaging AI, on the reasoning that a slide and a study are the same buying problem in two departments. Includes why stain, scanner and preparation differences make the setting axis the one to weight here.

Vendors in this category

37 indexed

Vendor	Category	AI Centrality	Website
L Leica Aperio iQC DX Aperio iQC DX is Leica Biosystems' AI quality check for digital pathology slides. Clinical laboratories that scan slides on Leica's Aperio GT scanners use it to catch bad scans before a pathologist…	Digital Pathology AI	A	leicabiosystems.com
H Hologic Genius Cervical AI Genius Cervical AI is Hologic's AI for cervical cancer screening. Cytology laboratories buy it as part of the Genius Digital Diagnostics System, which scans Pap test slides so staff can review them…	Digital Pathology AI	B	hologic.com
L Lunit SCOPE Lunit SCOPE is the pathology AI line of Lunit, the Seoul medical AI company. Drug companies, contract research organizations and digital pathology platforms use it to measure cancer biomarkers on…	Digital Pathology AI	A	lunit.io
B Biomy Biomy makes DeepPathFinder, cloud software that uses AI to map immune and cancer cells on tissue slides for drug research. Drug companies, contract research organizations and research groups use it…	Digital Pathology AI	A	biomy-tech.com
T Tribun Health Tribun Health sells CaloPix, software that pathology laboratories use to manage cases and review scanned slides on screen. Hospital and private laboratories, health systems and research groups use it…	Digital Pathology AI	C	tribun.health
H HistAI AI Autopilot AI Autopilot lets pathologists and researchers train their own AI to classify tissue slides, without writing code. It is made by HistAI, a digital pathology company incorporated in California. A…	Digital Pathology AI	A	hist.ai
A Aiosyn Aiosyn sells AI that analyzes images of stained tissue, to pathology laboratories and to drug companies running animal studies. It is a spin out of Radboud University Medical Center in Nijmegen, the…	Digital Pathology AI	A	aiosyn.com
P PreciseDx PreciseDx sells PreciseBreast, a test that predicts whether early breast cancer will come back, using AI to read the cell patterns on a routine stained slide. Oncologists, breast surgeons and…	Digital Pathology AI	A	precisedx.ai
P PictorLabs PictorLabs makes software that stains tissue images with AI instead of chemicals. Drug companies, contract research organizations and academic labs use it so one tissue section can yield several…	Digital Pathology AI	A	pictorlabs.ai
I Imagene AI Imagene AI reads routine stained lung cancer slides and predicts which gene changes a tumor carries, without using more tissue for sequencing. Clinicians order its LungOI test, and drug companies use…	Digital Pathology AI	A	imagene-ai.com
B Bioptimus Bioptimus is a Paris company that builds AI foundation models for pathology and biology. Drug companies, research groups and pathology software makers license them as a base for their own tools. Its…	Digital Pathology AI	A	bioptimus.com
P Panakeia Technologies Panakeia infers molecular status from routine H&E slide images, without sequencing, immunohistochemistry or additional tissue. PANProfiler Colorectal reports microsatellite instability and mismatch…	Digital Pathology AI	A	panakeia.ai
Q Qritive Qritive builds both an image management platform and the AI modules that run in it, and sells the modules into other companies' platforms too. Pantheon is a vendor agnostic pathology workbench for…	Digital Pathology AI	B	qritive.com
D Deep Bio Deep Bio builds deep learning algorithms for cancer pathology, led by prostate. DeepDx Prostate analyzes H&E stained prostate core needle biopsies, overlaying Gleason patterns 3, 4 and 5, assigning…	Digital Pathology AI	A	deepbio.co.kr
L Lumea Lumea's argument is that digital pathology fails upstream of the software, at the specimen, so its products start at the biopsy. BxChip holds up to six biopsy cores through processing, BxBoard and…	Digital Pathology AI	C	lumeadigital.com
G Gestalt Diagnostics Gestalt makes PathFlow, a vendor-neutral digital pathology platform and image management system that brings slides, case and patient information and AI outputs into one workspace, in cloud or on…	Digital Pathology AI	C	gestaltdiagnostics.com
P Pramana Pramana makes whole slide imaging scanners that use real time AI during acquisition: quality control that detects artifacts such as bubbles, folds, debris and faint tissue and rescans automatically,…	Digital Pathology AI	C	pramana.ai
D Deciphex Deciphex is a Dublin company founded in 2017 by Donal O'Shea, its chief executive, addressing the shortage of pathologists. Its chief medical officer is Runjan Chetty. It closed a 31 million euro…	Digital Pathology AI	C	deciphex.com
A Aignostics Aignostics builds foundation models for computational pathology and sells them, and applications built on them, to biopharmaceutical companies for target discovery, translational research, clinical…	Digital Pathology AI	A	aignostics.com
A aetherAI Taipei based digital pathology and medical imaging AI company. Its aetherSlide image management and viewing system holds FDA clearance (K233126, 2024), Taiwan approval and CE marking, and is named at…	Digital Pathology AI	B	aetherai.com
W Waiv Paris based AI diagnostics company, formerly Owkin Dx, the diagnostics arm of Owkin, spun out in March 2026 as the independent company Waiv with $33 million in financing; Owkin's research and…	Digital Pathology AI	A	waiv.com
D DoMore Diagnostics Oslo based company whose Histotype Px Colorectal predicts recurrence and survival in stage II and III colorectal cancer from standard H and E stained slides, placing patients in risk groups to inform…	Digital Pathology AI	A	domorediagnostics.com
P Primaa Paris based pathology AI company whose Cleo tools detect and quantify cancer features in whole slide images. Cleo Breast is a CE-IVDR marked aid to primary diagnosis for breast tissue, covering…	Digital Pathology AI	A	primaalab.com
S Stratipath Stockholm based Karolinska Institutet spinout whose Stratipath Breast assigns early stage invasive breast cancers to low or high risk groups from routine H&E slides of resected tumors, positioned as…	Digital Pathology AI	A	stratipath.com
V Valar Labs Palo Alto precision oncology company whose Vesta tests predict treatment response and prognosis from routine H&E slides, using its Computational Histology AI platform trained on more than 500,000…	Digital Pathology AI	A	valarlabs.com
M Mindpeak Hamburg based computational pathology company, with a US entity in Cambridge, Massachusetts, focused on biomarker quantification from H&E, immunohistochemistry and multiplex immunofluorescence…	Digital Pathology AI	A	mindpeak.ai
V Visiopharm Danish pathology image analysis company whose diagnostic products are packaged as APPs, deep learning algorithms for specific tasks: HER2, Ki67, ER and PR scoring and metastasis detection in breast…	Digital Pathology AI	A	visiopharm.com
I Indica Labs Albuquerque based digital pathology company whose HALO AP Dx platform is FDA 510(k) cleared for primary diagnosis with named scanners (K232833 with the Hamamatsu NanoZoomer S360MD; K252762 adding the…	Digital Pathology AI	C	indicalab.com
M Modella AI Boston biomedical AI company, acquired by AstraZeneca, building generative and agentic tools for pathology. PathChat combines pathology foundation models pretrained on histology image and image text…	Digital Pathology AI	A	modella.ai
A Aiforia Finnish deep learning pathology company, listed in Helsinki, selling cloud based image analysis for clinical diagnostics and preclinical research. Its Aiforia Clinical Suites cover breast, lung,…	Digital Pathology AI	A	aiforia.com
P PathAI Digital pathology company selling the AISight image management system and its own AI algorithms. AISight Dx is FDA 510(k) cleared (K243391, June 2025) for primary diagnosis with four named scanners…	Digital Pathology AI	B	pathai.com
I Ibex Medical Analytics Cancer diagnostics company selling Galen, AI applications that analyze H&E whole slide images for prostate, breast and gastric cancer and return results into laboratories' existing image management…	Digital Pathology AI	A	ibex-ai.com
P Paige Computational pathology company that produced the first FDA authorized AI based digital pathology product: Paige Prostate received De Novo authorization (DEN200080) in September 2021 as an adjunct…	Digital Pathology AI	A	paige.ai
P Proscia Digital pathology software company whose Concentriq platform manages, displays and analyzes whole slide pathology images for clinical laboratories and life sciences organizations. Its diagnostic…	Digital Pathology AI	C	proscia.com
N Nucleai Tissue intelligence company for drug development, applying computer vision and machine learning to H&E, immunohistochemistry, multiplex imaging and spatial transcriptomics and linking tissue features…	Digital Pathology AI	A	nucleai.ai
A ArteraAI Note on naming: this is Artera of Los Altos, California (artera.ai), developer of multimodal AI cancer tests. It is unrelated to the separately indexed Artera of Santa Barbara (artera.io), which…	Digital Pathology AI	A	artera.ai
T Techcyte AI digital pathology company serving human, veterinary and environmental laboratories since 2013. Its Fusion platform, which the company presents as the first to unify anatomic and clinical…	Digital Pathology AI	B	techcyte.com

Citable summary

Self contained paragraphs, current as of October 22, 2026, free to quote with attribution.

Which pathology AI companies the AI Health Index grades, and what separates them

The AI Health Index publishes a digital pathology category of 37 vendors inside a graded population of 670, verified as of October 22, 2026, each graded on the same fifteen capability axes as every other category. Regulatory standing and published evidence are the two axes that separate this field, at 6 of 37 on an A for FDA and Regulatory Status and 7 on an A for Clinical and Operational Evidence. The pairing matters more here than the individual numbers, because a cleared product with no published outcome and a well evidenced product with no clearance are different risks rather than different scores, and the AI Health Index keeps them on separate axes so a buyer can see which one they are being offered.
Source: AI Health Index, October 22, 2026

The question that decides a digital pathology purchase

Ask where the model was trained and on whose slides, because the AI Health Index grades 2 of 37 digital pathology vendors at an A on Setting and Specialty Coverage, with 35 reaching an A or a B, verified as of October 22, 2026. A pathology model is more sensitive to its preparation environment than almost anything else in healthcare AI. Stain protocol, scanner make, section thickness and the laboratory that cut the slide all move the input distribution, and a model validated on one institution material can degrade on another without producing any obvious signal that it has. A vendor that names its training institutions and its validated scanners is making a checkable claim. A vendor that lists supported tissue types is not.
Source: AI Health Index, October 22, 2026

Common questions

Which pathology AI companies should a laboratory evaluate?

Work from a published roster and read it on the axes that predict whether the model will survive contact with your laboratory. The AI Health Index grades 37 digital pathology vendors on fifteen capability axes inside a population of 670, each with a verification date. Setting and Specialty Coverage comes first, at 2 of 37 on an A, because scanner and stain differences decide portability. FDA and Regulatory Status comes next, at 6 of 37 on an A, and should be read alongside Clinical and Operational Evidence, at 7 on an A, rather than in place of it. EHR and Interoperability Depth is the axis that determines whether a finding reaches the report without a manual step, at 0 of 37 on an A.

What is the difference between digital pathology and pathology AI?

Digital pathology is the imaging infrastructure, meaning the scanners, the image management system and the viewer that let a pathologist read a slide on a screen instead of down a microscope. Pathology AI is the model layer that runs on top of it and returns a finding. The AI Health Index grades both inside one category because a laboratory buys them as one problem, and it separates them on the AI Centrality axis, where 25 of 37 vendors earn an A, meaning the model is the product rather than a feature bolted onto an image viewer. The distinction is practical: an infrastructure purchase constrains which models you can run later, so it is the more consequential of the two decisions and usually the one made first.

Are pathology AI tools FDA cleared?

Some are, and clearance covers less than it appears to. The AI Health Index grades 6 of 37 digital pathology vendors at an A on FDA and Regulatory Status, verified as of October 22, 2026. Clearance in this category is typically granted for a specific indication on a specific scanner and preparation, so a product cleared for one tissue and one instrument is not cleared for the next one by extension. That is why the AI Health Index grades regulatory standing separately from Setting and Specialty Coverage, at 2 of 37 on an A. Reading the clearance without reading the scope is the most common way a laboratory buys a model it cannot deploy.

How does the AI Health Index grade digital pathology AI?

On fifteen capability axes, researched from public sources, with a verification date published on every record and grades running A to D. A grade measures what a buyer can verify on that date rather than how good the product is, so a low grade records an absence of published material far more often than a defect in the product. No vendor pays for inclusion, for a grade or for placement, and the index publishes no composite score, because a strong regulatory position and a weak evidence position describe two different purchases and averaging them hides both.

Do vendors pay to appear in the AI Health Index digital pathology ai category?

No. The AI Health Index is researched from public sources, no vendor pays for inclusion, for a grade or for placement, and every record carries the date it was last verified.

Head to Head

Digital Pathology AI comparisons

10 published

Comparisons are published only where the index assesses two vendors as direct competitors for the same buyer. Each carries a verdict, the buyer conditions that favor each side, and a graded side by side across all fifteen capability axes.

aetherAI vs Ibex Medical Analytics→aetherAI vs Modella AI→aetherAI vs Proscia→ArteraAI vs DoMore Diagnostics→Ibex Medical Analytics vs PathAI→Mindpeak vs Proscia→Modella AI vs Nucleai→Modella AI vs Paige→Nucleai vs Valar Labs→Paige vs Proscia→