Radiology & Imaging AI

Infrastructure for building medical imaging AI rather than a clinical application, which makes it structurally different from every other vendor in this lane. Grace is a multimodal foundation model supporting image to image and text to image learning across X-ray, CT, MRI, and echocardiography, trained on over a petabyte of permission based anonymized imaging studies enriched with corresponding reports across 2D, 3D, and longitudinal series. The HOPPR AI Foundry is the surrounding development environment, combining accelerated computing, curated datasets, foundation models, fine tuning tooling, and traceable development workflows inside a stated HIPAA compliant environment, so developers, radiology PACS vendors, and AI companies can build, evaluate, fine tune, validate, and host imaging models without assembling that infrastructure themselves. NVIDIA open models NV-Reason and NV-Generate became available on the Foundry in March 2026, with NV-Reason generating structured analytical reasoning alongside outputs. The MC Chest Radiography Narrative Model, introduced April 2026, is a vision language model translating chest X-rays into structured descriptive text, shipped with training data traceability records and version locking so developers can reproduce results. Forward Deployed Services pairs HOPPR machine learning staff with customer teams for fine tuning. Founded 2019, led by Dr Khan Siddiqui; $34.5 million raised including a $31.5 million Series A in June 2025, with Health2047, the American Medical Association venture studio, among investors.

AI for gastroenterology across two product lines. SKOUT is a real time computer aided polyp detection device that received FDA 510(k) clearance in 2022 for adults undergoing colorectal cancer screening or surveillance, applying computer vision to endoscopic video to flag suspicious tissue during the procedure. In a randomized controlled trial published in Gastroenterology, SKOUT demonstrated a 27 percent relative increase in adenomas detected per colonoscopy, and the company states it was evaluated in the largest US based multicenter clinical study completed for a computer aided detection device in this category. The vendor reports the device does not extend total procedure or withdrawal time. Distribution runs through an exclusive partnership with Provation, a GI documentation vendor reporting more than 3,500 customer facilities. The second line, Clinical Trial Optimization and AI Recruitment, applies machine learning to endoscopic image scoring and patient identification for inflammatory bowel disease trials, serving life sciences sponsors rather than providers.

Clinical AI for imaging triage, delivered through aiOS, an enterprise AI operating system that handles data normalization, continuous performance monitoring, and governance so health systems can run multi condition AI without re architecting infrastructure. In January 2026 the FDA cleared what the company describes as healthcare's first comprehensive AI triage solution, powered by CARE (Clinical AI Reasoning Engine), its self developed foundation model. The clearance brought 11 newly cleared indications together with three previously cleared into a single abdomen CT workflow, 14 in total, and per the FDA reviewed pivotal study the new indications reported a mean sensitivity of 97 percent and mean specificity of 98 percent, with the company reporting roughly an order of magnitude reduction in false alerts against single condition tools. The company reports more than 100 million patient cases analyzed on aiOS. A successor model, CARE2, has been announced, and a multi year collaboration with Amazon Web Services supports the foundation model work. Co founded and led by Elad Walach.

Generative AI for radiology reporting and follow up. Omni Impressions generates a report impression from the radiologist's dictated findings, learning each radiologist's language preferences from their historical reports. Omni Reporting auto fills structured templates from natural dictation, and Omni Unchanged pulls stable findings forward from prior reports, which the vendor reports cuts follow up dictation time by half using up to 90 percent fewer words. Continuity tracks incidental findings through to completed follow up; the vendor reports health systems using it improved follow up exam completion from roughly 30 percent to over 75 percent. Works inside existing PACS, RIS, and EHR systems. Series C reached $68 million including strategic investments from four health systems.

Dental AI for radiographic pathology detection. Not to be confused with Pearl Health, a separate company in value based care intelligence also indexed here. Second Opinion analyzes bitewing, periapical, and panoramic radiographs in real time at chairside, highlighting up to 18 findings per image including caries, bone loss, calculus, periapical radiolucencies, and defective restoration margins. Second Opinion 3D extends the platform to CBCT, making Pearl, per the company, the first dental AI company with FDA clearance for both 2D and 3D radiologic analysis. Additional clearances cover pediatric caries detection from age four and AI segmentation. The panoramic clearance was supported by a standalone performance study and a fully crossed multi reader multi case study. The company reports regulatory clearance in 120 countries and a published study in which operator diagnostic accuracy rose from 82 percent to 98 percent with the tool. Founded 2019 by Ophir Tanz.

Deep learning software that enhances and accelerates medical image acquisition on existing scanners rather than detecting pathology. SubtlePET (FDA cleared 2018) and SubtleMR (2019) denoise and sharpen PET and MRI images, allowing faster and lower dose acquisition; SubtleHD (MR) cleared November 2025 and SubtleHD (PET) cleared May 2026 extend that with newer model architectures, with SubtleHD (PET) supporting all FDA approved radiotracers and, per the vendor, up to 75 percent faster PET imaging. A CT product has clearance pending. The company reports 11 FDA clearances, more than 25 peer reviewed publications, and deployment on more than 1,300 scanners, with customers including Mount Sinai, RadNet, and Radiology Partners. Raised $33 million in growth capital anchored by a Series C led by Morgan Stanley Expansion Capital in 2026.