PathAI

Paid

PathAI is AI-powered digital pathology software for healthcare organizations. It sits in healthcare work, where pathologists need to manage and analyze tissue slides at scale.

The core product is AISight, a cloud-native platform for image management, case management, and AI-assisted analysis. AISight Dx has FDA clearance for primary diagnosis. The company also offers AI algorithms for biomarker quantification and drug development services for biopharma clients.

The platform needs existing digital infrastructure to work: whole-slide scanners, laboratory information systems, and storage. It is not a standalone tool you open on a laptop.

Open it if you run a large pathology lab, hospital system, or clinical trial program. Skip it if you are an independent pathologist or small practice.

It helps most when scale and regulatory rigor matter more than speed of setup.

• Clinical pathologists with high slide volumes: You get automated cell classification and tissue structure identification. You still verify outputs against source slides.
• Medical laboratory teams managing large portfolios: You get unlimited slide processing and enterprise security standards. You need custom enterprise contracts and integration work.
• Large hospital systems building digital infrastructure: You get remote case review across distributed networks. You need cloud-native architecture and existing scanner hardware.
• Research institutions wanting AI collaboration: You get partnerships that refine algorithms with real clinical data. You need to contribute pathologists and commit to multi-year relationships.
• Biopharma companies running oncology trials: You get standardized biomarker quantification for PD-L1, HER2, and drug development tool qualification. You need CLIA-certified lab services and trial support infrastructure.
• European clinical labs needing CE-IVD marked platforms: You get regulatory-compliant diagnostic use. US labs get research-use-only versions without diagnostic clearance.
• Pharma teams developing companion diagnostics: You get FDA-qualified measurements accepted in actual drug trials. You need multi-month implementation and enterprise procurement.
• Pathology labs transitioning to digital workflows: You get scanner-neutral compatibility and LIS integration. You need existing physical infrastructure before you can start.

These are the parts you notice after you are through the setup.

• Scanner-neutral image management: It works with Leica, Hamamatsu, Phillips, and others. You are not locked into one hardware vendor.
• FDA-cleared algorithms: 20+ cleared or research-grade algorithms cover HER2 scoring, tumor microenvironment analysis, and liver disease. You can cite regulatory acceptance.
• Predetermined Change Control Plan: You update AI models without full FDA resubmission each time. You move faster than standard clearance timelines.
• Biomarker quantification for trials: It replaces subjective glass-slide reviews with standardized PD-L1, tumor-infiltrating lymphocyte counts. You get consistent measurements across sites.
• Remote access for distributed teams: Pathologists review cases from anywhere without physical microscopes. You keep talent that does not relocate.

Skip it when any of these are true.

• No self-serve entry: You need custom enterprise contracts and procurement engagement. There is no public pricing or free trial.
• Integration-heavy setup: Laboratory database integration needs coordination and months of work. You cannot open it and start today.
• Requires existing infrastructure: You need whole-slide scanners, LIS systems, and storage already in place. It does not digitize your lab for you.
• Not autonomous: AI outputs require clinical verification. You still check every case against source slides.
• Post-acquisition uncertainty: Roche acquired PathAI in May 2026. Future roadmap and independent operations are unclear.