Medical AI company
Proscia
Philadelphia digital pathology company behind Concentriq, an AI platform used by diagnostic labs and biopharma.
Company overview
Proscia develops Concentriq, a pathology AI platform used by diagnostic laboratories and biopharmaceutical organizations for image review, AI deployment and computational pathology in drug development. The company states it is being acquired by Agilent Technologies.
- Headquarters
- Philadelphia, United States
- Founded
- 2014 source
- Company type
- AI Technology Developer, Healthcare IT Provider, Platform Provider
- Status
- Established Company
In its own words: “Proscia is the digital pathology company behind Concentriq, helping pathology teams advance precision medicine from discovery to diagnosis.” source
AI products and platforms
- ConcentriqAI-powered
Pathology AI platform for digital review, AI deployment and computational pathology across labs and biopharma.
Product page ↗
Technology categories
Clinical applications
- digital pathology review
- AI deployment in labs
- computational pathology for clinical trials
Relationships
- Partner Visiopharm source
Relationships are shown as stated on the cited page; the other party may not confirm them.
Official sources
Last verified 29 October 2026 against the sources above.
Questions about Proscia
What are whole-slide images in digital pathology?
A whole-slide image (WSI) is a high-resolution digital scan of an entire glass pathology slide, which can be viewed and navigated on screen at different magnifications, much like a microscope.
WSIs are very large files, often gigabytes per slide, so digital pathology needs fast scanners, substantial storage, network capacity and viewing software. They are the input for pathology AI.
FDA describes a whole slide imaging system as an automated digital slide creation, viewing and management system intended as an aid to the pathologist to review and interpret digital images of surgical pathology slides. Formats vary between scanner vendors, and DICOM has been extended to support whole-slide imaging, which helps interoperability between scanners, archives and AI tools.
What is AI image reconstruction and denoising?
AI image reconstruction and denoising use deep learning to produce clearer images from raw scanner data or to reduce noise and artifacts, for example in CT or MRI. Vendors often position these tools as supporting lower-dose or faster scanning protocols.
Unlike detection software, these tools change the image the clinician reads rather than adding a finding. Questions to ask include:
- Is the function built into the scanner or a separate software product?
- Which scanners, protocols and body regions is it authorized for?
- How was diagnostic image quality evaluated, and could fine detail be lost or altered?
These functions are typically regulated as part of the imaging device or as image processing software, depending on the product and market.
What is AI-powered medical image analysis?
AI-powered medical image analysis uses machine learning, often deep learning, to process images and return outputs such as detected regions, segmentations, measurements, quantitative scores or classifications.
It is used beyond radiology, including in cardiology (echocardiography), pathology (whole-slide images), dentistry (intraoral and panoramic radiographs), ophthalmology (retinal photographs and OCT) and dermatology. Outputs may be shown as overlays, structured results or notifications.
Because the software analyzes medical images, in the US it does not meet the criteria for non-device clinical decision support, and image analysis with a medical purpose is commonly regulated as a device. The Medical Imaging AI category in the Medical AI directory covers these companies.