One platform, end to end
XRS-AI helps radiology teams prioritise urgent studies, manage reading and annotation operations, close the loop on AI feedback, and maintain an enterprise-grade evidence trail across every action, from case intake to final sign-off, in one modern browser-based workspace.
Prioritise critical studies
Surface urgent cases, monitor SLA risk, and route studies to the right reader with AI-informed triage and live operational dashboards covering queue, coverage, deadlines and throughput.
Close the AI feedback loop
Capture radiologist confirmations, overrides and annotation labels to build auditable datasets for continuous model improvement, with a retrain monitor, dataset builder and human-in-the-loop training studio.
Govern every action
Role-based access, immutable-style audit trails, data lineage and chain-of-custody features support regulated imaging teams and preserve a record of which studies feed each training dataset.
DICOM-aware & integration-ready
Built as a React/TypeScript PWA on a Node/Express API with PostgreSQL, Redis queues, S3-compatible object storage, DICOMweb connectivity and a Microservices Engine for workflow automation, with FHIR- and HL7-ready interfaces and PACS/RIS integration patterns.
Forensic & medico-legal extensions
Optional modules support evidence handling, DVI workflows, integrity anchors, forensic reporting and chain-of-custody review, extending the platform from clinical radiology into medico-legal imaging.
