We're at RSNA 2024! Visit us at Booth 5645 in South Hall Level 3.

AI-powered reporting and annotation for radiology

Accelerate the development and deployment of medical imaging AI with DICOM-native data annotation tools. Supercharge your reporting workflows with AI and unlock extra efficiency and productivity.

Stanford
Northwestern
Philips
UCSF
Johnson & Johnson
Cleveland Clinic
National Institutes of Health
University of Alabama
Mayo Clinic
RSNA
Bayer
Emory Healthcare
REPORTING

Leapfrog into the future of medical AI workflows

Supercharge clinical reporting workflows with LLMs to unlock extra efficiency and productivity. Automatic template selection, key findings dictation mapping, impression generation, proofreading, and more. Streamline administrative tasks with automated billing code generation. Improve patient communication and education with patient-friendly audio messages.

Simple HL7/DICOM integration with EHR/HIS/RIS

Works on desktop, laptop, tablet, or mobile

Multi-device sync

AI-driven or traditional reporting modes

Multilingual support

Contextual AI chat

Reporting Product
ANNOTATOR

Build high-quality datasets and models

Our platform has enabled thousands of doctors and their collaborators to create large high-quality labeled datasets, deploy and validate their models, and build AI-driven clinical workflows.

Native DICOM support

FDA 510(k)-cleared viewer

Seamless scaling

AI-assisted annotation

PHI detection and De-ID

Developer APIs

Annotator Product

Contact Us

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