AI PACS
DICOM-native worklists, viewers, AI launch controls, and reporting surfaces in one clinical workspace.

AI imaging platform
RAI PACS turns clinical imaging into a secure, longitudinal intelligence layer for radiology operations, preventive screening, model-ready datasets, and population health analytics.
Operating layer
The platform keeps the day-to-day clinical workspace intact while adding the data, AI, and analytics capabilities needed for precision and preventive medicine.
Modules
DICOM-native worklists, viewers, AI launch controls, and reporting surfaces in one clinical workspace.
Structured storage for studies, reports, metadata, and AI outputs across sites and modalities.
Patient-level imaging timelines that make interval change, follow-up, and response visible.
Repeatable organ, tissue, and lesion measurements ready for clinical review and research.
Preventive risk signals surfaced from routine scans for clinician-controlled triage.
Cohort views for risk, capacity, outcomes, and imaging-driven preventive medicine programs.
Clean, governed, labeled imaging datasets prepared for validation and model development.
A living imaging profile that connects anatomy, measurements, history, and risk over time.
Workflow
Connect PACS, VNA, modality, and report sources while preserving DICOM context.
Standardize metadata, series structure, study quality, and clinical references.
Run AI pipelines for organ, lesion, and tissue measurements with reviewable outputs.
Move findings into worklists, reports, cohorts, and preventive care programs.
Ready for deployment
Keep radiologists and clinicians in a familiar study-centric flow, then extend the same imaging foundation into research datasets, AI-assisted quantification, and preventive care operations.



RAI PACS
Continue to the secured worklist, patient registry, viewer, and AI reporting tools.