# PathAI

Source: https://onco.cc/companies/pathai/  
OnCo record `pathai` (Company). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

PathAI runs the AISight AI pathology platform and quantifies biomarkers for pharma trials.

## Summary

PathAI, based in Boston, runs the AISight AI pathology platform and quantifies biomarkers for pharmaceutical trials. Its products include AISight image management, the AIM-PD-L1 and AIM-HER2 quantification algorithms and TumorDetect, backed by large pharma partnerships, and its PLUTO foundation model has its own OnCo record. OnCo links it to digital pathology and to bottlenecks on unvalidated AI, unstandardised biomarkers and the shortage of pathologists, and to ideas including a standard evaluation pathway for AI pathology and one digital PD-L1 scale that maps across competing assays. Whether AI biomarker scoring becomes the regulatory standard for trial enrolment is the open question. The digital pathology page carries the wider picture.

## Fields

- Kind: Company
- Last checked: 2026-09-04
- HQ: Boston, MA
- Type: ai-software
- Website: https://www.pathai.com

## Sources

- Official website: https://www.pathai.com

## Connected records

- fronts: [AI & Computation](https://onco.cc/fronts/ai-computation/)
- technologies: [Digital pathology & AI](https://onco.cc/technologies/digital-pathology-ai/), [PLUTO (PathAI)](https://onco.cc/technologies/pluto/)
- bottlenecks: [AI that is built but not validated or deployed](https://onco.cc/bottlenecks/b-ai-validation/), [Biomarkers are not validated or standardised](https://onco.cc/bottlenecks/b-biomarker-validation/), [Not enough oncologists, nurses, pathologists, physicists](https://onco.cc/bottlenecks/b-workforce/)
- ideas: [A pre-competitive consortium to train a shared multimodal cancer foundation model](https://onco.cc/ideas/idea-data-precompetitive-cancer-foundation-model/), [A standard evaluation pathway for AI-assisted pathology, from reader study to deployment](https://onco.cc/ideas/idea-data-ai-pathology-evaluation-standard/), [AI second reads to stop borderline lesions being upgraded to cancer](https://onco.cc/ideas/idea-prev-pathology-ai-borderline-anchor/), [AI-first reading for high-volume common cancer diagnoses, pathologist for the exceptions](https://onco.cc/ideas/idea-acc-ai-first-pathology-common-cases/), [One digital PD-L1 scale that maps across all the competing assays](https://onco.cc/ideas/idea-tr2-pdl1-digital-calibration/), [Version control and locked reference sets for AI algorithms used as companion diagnostics](https://onco.cc/ideas/idea-tr2-ai-cdx-change-control/)
- roadmaps: [AI in oncology roadmap: pattern readers → foundation models → agents in the workflow](https://onco.cc/roadmaps/ai-oncology-roadmap/)

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JSON: https://onco.cc/api/v1/entities/pathai.json