AI-powered pathology for faster, more accurate disease diagnosis
PathAI is an AI-powered pathology platform for disease analysis and biomarker quantification.
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AI Editor ApprovedApproved and published by our AI Editor-in-Chief after full panel analysis.PathAI is an AI-powered pathology platform for disease analysis and biomarker quantification. Pharmaceutical companies, clinical laboratories, and research institutions use its machine learning tools to assist pathologists in analyzing tissue samples and identifying disease patterns across clinical diagnostics, drug development, and research workflows. Pricing is quote-based across its platform, biopharma services, and fee-for-service diagnostics offerings. Key capabilities include the AISight digital pathology platform, AIM-MASH AI Assist for clinical trials, the AISight Dx platform cleared for primary diagnosis, IBDExplore, biopharma lab services, and case and image management. TopReviewed's six-seat AI review panel scored it 7.9/10, praising the first FDA-qualified AI tool for MASH clinical trials backed by 32.5 million pathologist annotations and a 450-member pathology network, while noting there is no public pricing, trial, or self-serve path. It best fits biopharma companies running oncology, IBD, or MASH trials that need FDA-credentialed histopathology endpoints.
PathAI is a Boston-based company that develops AI-powered software for digital pathology. Its platform is designed to help pathologists and researchers analyze whole-slide images of tissue samples with greater speed and consistency. By applying machine learning models trained on large datasets of annotated pathology images, PathAI aims to reduce diagnostic variability and improve the accuracy of disease detection and grading.
The platform serves two primary markets: biopharma and clinical pathology. For pharmaceutical and biotechnology companies, PathAI offers tools to support companion diagnostics development, clinical trial patient selection, and biomarker quantification. These capabilities are intended to help drug developers better stratify patient populations and evaluate treatment responses in oncology and other disease areas.
On the clinical side, PathAI offers products under the AISight brand, which is a digital pathology ecosystem designed for clinical laboratories transitioning to digital workflows. This includes image management, quality control tools, and AI-assisted analysis integrated into the pathologist's review process.
PathAI's models cover a range of disease areas including oncology, liver disease (MASH), inflammatory bowel disease, and celiac disease. The company develops these models in collaboration with academic medical centers and industry partners, building disease-specific algorithms that are validated against pathologist consensus annotations.
PathAI operates primarily as an enterprise solution, working with large pharmaceutical companies, contract research organizations, and hospital laboratory systems. Pricing and access are managed through direct commercial agreements, and the platform is not offered as a self-service consumer product.
In May 2026 Roche signed a definitive merger agreement to acquire PathAI; once the deal closes (expected in the second half of 2026), PathAI becomes part of Roche's Diagnostics division.
Machine learning algorithms trained and validated using 32.5 million+ annotations from a contributor network of 450+ board-certified pathologists to analyze digital pathology images for biomarker discovery and drug development.
A clinical trials platform tool providing standardized histopathology endpoints for ulcerative colitis studies.
An FDA-qualified AI-powered tool designed specifically for use in MASH clinical trials, representing the first AI tool to receive FDA qualification for this indication.
A research-use AI panel of histopathology features that spatially characterizes the inflammatory microenvironment in inflammatory bowel disease.
Centralized digital case and image management system integrated within AISight® to streamline laboratory workflow operations.
PathAI's network of digital anatomic pathology laboratories running the AISight® platform, giving member labs early access to new PathAI algorithms and a framework to contribute de-identified pathology data to biopharma research and evidence-generation studies.
A cloud-native, open platform enterprise workflow solution that serves as a central hub for case management, image management, and AI tools to enable multiple histopathology use cases.
An FDA-cleared digital pathology platform cleared for primary diagnosis, deployed by clinical laboratories including Labcorp nationwide.
Pathology laboratory services supporting every phase of drug and diagnostic development for biopharma companies.
A dedicated platform within AISight® that supports biopharma clinical trials by delivering standardized histopathology endpoints and AI-assisted analysis.
Cloud-native enterprise workflow platform for hospitals, clinical labs, academic medical centers, reference laboratories, and health systems. Pricing requires contacting PathAI sales directly — no public rates are published.
Custom engagement for biopharma and pharmaceutical companies supporting clinical trials, biomarker discovery, and drug development. PathAI does not publish a fee schedule — contact PathAI sales for a quote.
Tailored solutions for organizations developing AI-powered companion diagnostics and Software as a Medical Device (SaMD). Pricing is not published and is negotiated directly with PathAI.
FDA-qualified AI pathology with real biopharma traction and zero self-serve entry.
“PathAI is a serious enterprise platform with validated clinical credentials, including the first FDA-qualified AI tool for MASH trials. It's not for every buyer — but for biopharma and large lab systems, it's a legitimate category leader.”
32.5 million annotations and an FDA qualification on AIM-MASH AI Assist. That's not marketing copy — that's a defensible moat. Labcorp deploying AISight® Dx for primary diagnosis nationwide tells you this isn't a proof-of-concept. PathAI's clinical trial infrastructure gives it a distinct lane.
The tradeoff is real: zero self-serve, no public pricing, no free trial. Every engagement goes through a sales cycle. That's fine if you're a pharma company running a MASH trial. It's a dealbreaker if you're a regional lab testing the waters.
The 450+ pathologist annotation network and 50M+ slide dataset are structural advantages that take years to replicate. Viability looks solid — enterprise contracts, FDA clearances, and named anchor customers don't happen at a startup running on fumes.
FDA qualifications and 32.5M annotations create a lead that peers in biopharma will notice.
First FDA-qualified AI tool for MASH trials is a board-friendly credential — adopting this won't raise eyebrows.
Enterprise-only, contact-for-pricing model means long procurement cycles before any workflow impact is realized.
AIM-MASH AI Assist and IBDExplore directly advance clinical trial differentiation, not just cost reduction on existing workflows.
FDA-cleared products, Labcorp as a named customer, and enterprise biopharma contracts signal a company with durable revenue and real institutional backing.
Biopharma companies running oncology or IBD clinical trials who need FDA-credentialed AI histopathology endpoints.
You're a mid-size regional lab without budget or bandwidth for a long enterprise procurement cycle.
The annotation corpus is the moat, and PathAI's biopharma-plus-clinical track keeps it compounding.
“PathAI has built a validated, regulatory-cleared foundation that distinguishes it from most AI diagnostics vendors still chasing their first clearance. The AISight Dx platform deployed by Labcorp and the FDA-qualified AIM-MASH tool signal enterprise-grade clinical credibility.”
The annotation corpus matters here. 32.5 million pathologist-validated annotations plus a 450-member pathologist contributor network isn't a marketing number — that's the moat. Other AI pathology vendors have cleared models too, but PathAI's dual-track architecture (biopharma CRO services plus clinical lab deployment) means the algorithm training feedback loop keeps compounding. If we adopt this for companion diagnostics and clinical trial endpoints, in 3 years we have a validated algorithmic infrastructure that's increasingly difficult to replicate or migrate away from.
The FDA qualification of AIM-MASH AI Assist is the most significant clinical signal in this portfolio. That's the first AI tool qualified for MASH trials — a genuinely hard regulatory milestone, not a 510(k) clearance for low-risk software. For any institution running GI or liver disease trials, that qualification changes patient stratification workflows in ways that matter to IRBs and sponsors alike.
The constraint is the enterprise-only, contact-sales model with no public pricing. Academic medical centers and mid-sized labs can't self-evaluate — procurement cycles will be long, and budget visibility is zero until deep in the sales process. Integration surface looks solid for labs already on AISight, but the open-platform claim needs validation against your scanner and LIS vendors before committing.
First FDA-qualified AI tool for MASH trials plus FDA-cleared AISight Dx for primary diagnosis gives PathAI regulatory credentials in both drug development and clinical diagnostics.
AISight Dx cleared for primary diagnosis and deployed by Labcorp means this fits actual clinical lab workflows, not just research environments.
Open-platform architecture and third-party scanner integration are documented, but I couldn't find public API documentation, and contact-only access limits pre-procurement technical diligence.
If you build clinical trial endpoints on PathAI's standardized histopathology platform, switching costs compound quickly — that's a strength if the partnership holds, a constraint if it doesn't.
FDA-qualified AIM-MASH and 32.5M+ annotations represent genuine algorithmic depth, not surface-level ML wrapped around commodity models.
Biopharma sponsors and large clinical lab systems that need FDA-qualified histopathology endpoints and are prepared for an enterprise procurement process.
Your institution needs transparent pricing, self-service evaluation, or rapid deployment outside a formal enterprise agreement.
32.5M annotations, zero public prices — enterprise opacity at its most complete.
“PathAI operates entirely behind a sales call. No sticker price, no tier comparison, no published overage rates.”
No pricing page. The site doesn't say how AISight is licensed, and BioPharma engagements carry no published fee schedule. No number, no billing unit, no rate card. That's not a pricing model. That's a negotiation.
50-seat finance model is impossible here. No anchor price exists. AISight Dx is FDA-cleared and deployed by Labcorp nationwide. That's real validation. But a lab not running Phase III trials still has no published entry point to budget against.
The FDA qualification for AIM-MASH AI Assist is a concrete differentiator — first in category. That has regulatory value biopharma will pay for. The tradeoff: procurement will fight every contract. No termination-for-convenience language visible, no auto-renewal window disclosed. Budget 6-12 months for legal review.
No billing structure is published for platform licensing, biopharma services, or diagnostics partnerships — each requires direct negotiation and prolonged procurement cycles.
Contract length isn't published, and no auto-renewal window, cancellation terms, or termination-for-convenience clause is publicly visible.
Zero public rates across every engagement type — contact sales required for every tier.
FDA-qualified AIM-MASH AI Assist and 32.5M+ annotations provide measurable clinical trial endpoints, but financial ROI framing is absent from public materials.
No published fee schedule for platform licensing or biopharma services, so multi-year cost stacks can't be modelled before a quote.
Large biopharma or health systems with dedicated procurement and regulatory teams running clinical trials in oncology, IBD, or MASH.
Your lab needs predictable annual spend and can't absorb a 6-month contract negotiation cycle.
Production-grade in Labcorp's labs, structurally out of reach for a community pathology practice
“PathAI is enterprise-grade digital pathology infrastructure built for labs and biopharma, not individual practitioners. AIM-MASH AI Assist is the first FDA-qualified AI tool for MASH trials — that's a genuine clinical landmark, not marketing copy.”
The 32.5 million+ annotation training set and the 450+ board-certified pathologist network tell you something real: the models were built with pathologist consensus, not scraped internet data. AISight Dx Platform is FDA-cleared for primary diagnosis and deployed by Labcorp nationwide — that's production-grade validation, not a pilot. AIM-MASH AI Assist carrying FDA qualification for MASH clinical trials is a genuine regulatory moat.
Day-three reality is where enterprise agreements show their shape. No self-service trial, no public pricing, no API docs visible — everything routes through a sales conversation. For a pathologist at a community hospital or a smaller CRO, the onboarding runway is long before a single slide gets analyzed. AISight Dx release notes land roughly every two months (v2.19 in March, v2.20 in May, v2.21 in July 2026), so development is visibly active; practitioner documentation is what I couldn't find.
The tradeoff is straightforward: PathAI is built for institutional workflows — biopharma clinical trials, large lab systems, companion diagnostic development. Surgically right for that buyer. Structurally inaccessible for everyone else.
AISight's cloud-native case and image management suggests stable daily workflow, but no trial access means day-3 friction is invisible until you're already contracted.
No public docs portal visible; PathAI publishes a blog and AISight release notes, but practitioner-facing technical documentation isn't accessible without a sales relationship.
No public API docs and contact-only pricing mean every workflow customization or integration question routes back through account management — a recurring friction point for in-house pathology teams.
Disease-specific algorithms across oncology, liver disease, and IBD — plus custom algorithm development for biopharma — signals real depth for power users operating at clinical trial scale.
AISight Dx Platform is FDA-cleared and deployed by Labcorp, indicating genuine integration into live clinical lab workflows rather than a parallel research sidecar.
Large clinical labs, biopharma clinical trial teams, and CROs needing FDA-qualified AI pathology integrated into institutional digital workflows.
You're a smaller pathology practice or academic group without a procurement team and budget for a negotiated enterprise agreement.
Workflow-scoped AI pathology tools with clinical-grade backing — and nothing to click until procurement signs
“PathAI is serious enterprise infrastructure for pathologists and drug developers, not a tool you browse on a Tuesday afternoon. The FDA qualification on AIM-MASH AI Assist is the kind of milestone that opens procurement conversations.”
The 32.5 million+ annotations backing the models isn't a marketing number — that's the kind of training scale that separates validated clinical tools from research demos. AIM-MASH AI Assist being the first FDA-qualified AI tool for MASH clinical trials is a concrete differentiator, and the EMA has qualified it too. The contributor network of 450+ board-certified pathologists is real infrastructure, not a vibe.
Daily polish is hard to grade when there's no self-serve trial and no pricing page. That's not a gap — that's the product category. Enterprise clinical software lives behind procurement, and AISight Dx being deployed by Labcorp nationwide suggests the workflow integration is real. Web-only platform is the expected form factor here; nobody's reading whole-slide images on a phone.
The tradeoff is straightforward: zero accessibility for anyone outside a biopharma or large lab context. No trial, no tiers, no solo researcher path. If you're a smaller CRO or academic center, you're negotiating a custom agreement before you see anything. That friction is industry-standard, but it's still friction.
AISight's cloud-native architecture and integrated case management suggest thoughtful workflow design, but no public UI access means this can't be observed directly.
Disease-specific tools like AIM-HI UC and IBDExplore suggest the platform is scoped by workflow rather than dumped on users as one giant feature set — that's a good sign for month-three usability.
Web-only platform is appropriate for whole-slide image analysis, but there's no evidence of any mobile companion for case review or notifications.
No free trial, no self-serve access, and contact-only pricing means onboarding starts with a sales call — that's the category norm but it's still homework before you see anything.
FDA clearance on AISight Dx and nationwide Labcorp deployment are strong signals that the platform holds up under clinical-grade load.
Biopharma companies running oncology or IBD clinical trials who need FDA-validated histopathology endpoints.
You're a solo researcher, small CRO, or academic lab without the procurement runway for a custom enterprise negotiation.
One FDA-qualified tool. Real regulatory moat. Enterprise lock-in is the tradeoff.
“PathAI has something rare: AIM-MASH AI Assist is the first FDA-qualified AI tool for MASH clinical trials. That's a durable credential, not marketing copy. But this is deep enterprise territory — no pricing, no trial, no self-serve anything.”
Three tells I check first. One: 32.5 million annotations cited — specific enough to be real. Two: AISight Dx is FDA-cleared for primary diagnosis, deployed at Labcorp nationwide — that's verifiable traction, not vaporware. Three: the FDA qualification for MASH is the kind of regulatory milestone that took years and doesn't get faked. Those are regulatory receipts, not adjectives.
The tradeoff is real: this is enterprise-only, contact-sales-only, no public pricing. Migration off AISight in 18 months means renegotiating custom agreements, re-validating algorithms, and potentially rebuilding trial endpoints. Exit portability is low by design — that's the nature of FDA-cleared SaMD partnerships, not a flaw exactly, but a commitment you don't reverse cheaply.
Honest take: came in expecting 'AI washing' in a hot category. The 450-pathologist annotation network and the Clinical Trials Platform with named indications (UC, IBD, MASH) changed my read. This isn't a demo product. It's slow, expensive, and sticky — which, for biopharma buyers, might be exactly right.
First FDA-qualified AI tool for MASH clinical trials is a concrete moat, and the EMA has qualified it as well.
Custom SaMD agreements, milestone-based contracts, and FDA-cleared workflows mean switching costs are structurally high — I couldn't find a documented standard export, or public docs for AISight Link, PathAI's open API.
Boston-based, Labcorp partnership, a $165M Series C, AISight release notes, and named enterprise clients suggest real organizational depth; the pending Roche acquisition settles runway but moves the roadmap inside a much larger company.
Claims anchor to specific FDA qualifications and named deployments — Labcorp, MASH qualification — rather than vague superlatives.
FDA-cleared AISight Dx and a Labcorp deployment match the pattern of durable healthcare IT vendors, not the pivot-and-die pattern I've seen from earlier digital pathology startups.
Large biopharma companies or health systems running regulated clinical trials that need FDA-qualified histopathology endpoints.
You need transparent pricing, quick deployment, or any realistic path to migrating off in under two years.
Common questions answered by our AI research team
Yes. AISight Dx holds FDA 510(k) clearance (K243391) for primary diagnosis in the US and is CE-IVD-marked in the EEA, UK and Switzerland. Its change control plan lets PathAI add scanners, displays and file formats without a new 510(k).
AISight Dx is FDA-cleared for primary diagnosis with the Leica Aperio GT 450 DX, Hamamatsu NanoZoomer S360MD, and Roche VENTANA DP200 and DP600 scanners. It is a cloud-native platform that runs across multiple lab sites.
Yes. AISight hosts partner algorithms from Deep Bio, DoMore Diagnostics, Mindpeak, Paige, Primaa, Stratipath and Visiopharm inside its single viewer and workflow, next to PathAI's own tools such as TumorDetect and ArtifactDetect.
Yes. AIM-MASH AI Assist scores MASH liver biopsies for trial enrollment and endpoints, and is the first AI pathology drug development tool qualified by both the FDA and EMA. It runs on the AISight Clinical Trials platform.
Yes. The AISight Clinical Trials platform is 21 CFR Part 11 compliant, GCP/GCLP compliant and ISO 27001 certified. It is a cloud-based SaaS platform for AI-assisted and remote central pathology reads in clinical trials.
Who PathAI competes with, and how each one differs
Paige focuses on FDA-cleared diagnostic AI models for specific cancers (e.g. prostate, breast) sold directly to pathology labs -- a narrower diagnostic-model line than PathAI's combined biopharma biomarker/clinical-trial services and open AISight image-management platform that hosts third-party algorithms.
Lunit is a Seoul-based, publicly traded (KOSDAQ) company spanning both radiology (chest X-ray and mammography triage) and pathology (Lunit SCOPE biomarker quantification), giving it a broader cross-modality imaging footprint than PathAI's pathology-only focus.
Proscia's Concentriq platform is primarily an image-management and workflow system that labs and pharma license to run their own or third-party AI algorithms on -- competing with PathAI's AISight IMS layer more directly than with PathAI's own diagnostic and biomarker AI models.
Ibex concentrates on live clinical deployment of cancer-detection algorithms (breast, prostate, gastric) sold directly to pathology labs, with a smaller footprint in the biopharma clinical-trial and companion-diagnostic biomarker work that makes up a larger share of PathAI's business.
PathAI is a Boston-based digital pathology and AI company that builds diagnostic tools and biopharma services to improve cancer detection and drug development.
