Rad AI

Rad AI is a radiology AI platform focused on the reading workflow: faster report creation, stronger impressions and tracked follow-up care. Built by radiologists and used by 200+ health organisations, it is sold to practices and health systems through a demo request rather than self-serve signup.

Rad AI is a radiology-focused AI platform built by radiologists for radiologists, aimed at the reading workflow rather than the imaging pipeline. The product is organised around three capabilities: reporting, impressions and continuity of care. Its stated goals are to help radiologists read faster, report with more confidence and close the loop on follow-up care, all inside a workflow designed to match how reading rooms actually operate. The reporting side addresses the drafting burden that consumes much of a radiologist's day, helping clinicians move from findings to structured report text with less manual keying. The impressions component targets the summary section of a report, the part that referring physicians read first and that carries the most clinical weight. Continuity covers downstream follow-up, so recommendations that appear in a report do not quietly disappear once the study is signed. Taken together, the three modules describe a single arc: generate the report, sharpen the conclusion, then track whether the recommended next step happened. The audience is clearly institutional. The site cites more than 200 health organisations among its users, with logos from large hospital systems, imaging groups and radiology practices, and the primary path to the product is a demo request rather than self-serve signup. That fits a category where procurement, IT review and clinical validation usually precede deployment. Practices evaluating Rad AI should expect a sales-led process and should plan for integration questions with existing PACS and reporting infrastructure, though the homepage does not detail which systems are supported. Among radiology AI vendors, Rad AI positions itself on the documentation and follow-up layer rather than on image interpretation or triage of scans. Buyers weighing options should treat it as a workflow and communication tool and judge it on reporting time saved, report quality and how reliably follow-up recommendations are tracked. The site also hosts a perspectives section, which is useful for understanding the company's clinical rationale before a demo conversation.