Viz.ai uses AI to detect disease on medical imaging and instantly coordinate care teams, speeding time to treatment for stroke and other emergencies.
Viz.ai analyzes CT, MR and other scans in seconds, flagging suspected findings such as large vessel occlusion stroke and alerting the right specialist on their phone. The platform synchronizes the care team around shared images and chat so decisions happen without waiting for phone calls or faxes. FDA-cleared algorithms cover stroke, cardiac and vascular indications, and the network now spans thousands of hospitals in the United States. Studies associate the platform with faster treatment times and improved patient outcomes.
Viz.ai is sold to hospitals and health systems through enterprise agreements, typically priced per service line or per study volume.
Stroke centers, cardiology programs and radiology departments that need faster specialist response and coordinated emergency care.
No. Viz.ai is a hospital-purchased clinical platform with contract pricing.
Yes. Viz.ai integrates with PACS, EHR and imaging systems, and offers technical interfaces for enterprise deployments.
Most imaging AI tools only flag findings; Viz.ai adds the coordination layer that mobilizes the care team, which is where the time savings come from.
Stroke centers use Viz.ai to detect suspected large vessel occlusion on CT and mobilize the neuro-interventional team before the radiologist’s final read. Cardiac programs coordinate aortic disease care with the same synchronized platform. Service-line leaders review analytics dashboards to measure door-to-treatment times and prove program impact to administrators. Networks of hospitals standardize emergency imaging response across sites with shared protocols inside Viz.ai.
Viz.ai is a hospital-purchased clinical platform requiring regulatory validation per indication, and its value depends on specialist response workflows that not every site has. Smaller facilities without interventional coverage may benefit less. Aidoc and RapidAI offer competing imaging triage, while PACS vendors are adding native AI triage modules.
Viz.ai connects to PACS and imaging modalities through DICOM workflows, then routes alerts to specialist mobile apps and care team channels. Hospital deployment requires clinical validation per indication, service-line agreement on response protocols and IT configuration of image transfer. The coordination layer β chat, image sharing, team rosters β is configured around existing on-call structures. Post-deployment analytics track response times and treatment metrics, which service-line leaders report to administration. Because the platform intervenes in emergency care pathways, drills and governance reviews are part of mature implementations.