Patient impact
See how Zauron identified >500 patients (of 3000 imaged) in need of treatment for one client
Proven value
See how Zauron identified revenue opportunities for clients to cover costs of care
Cutting edge of AI
See how Zauron is comprehensively revolutionizing Radiology
What if Peer Review actually worked to protect patients?
Zauron’s Peer Learning & Review software targets high probability false negatives that require a second radiologist look & sends weekly email alerts to radiologists review worklists with clickable links to our anonymized web based viewer.
Zauron’s Radiology AI finds errors that improve patient treatment quality & safety. We retrospectively audit exams for important incidental findings & deploy a persistent safety net for continued use. University of Texas has used Zauron to help 100s of patients & recover millions in reimbursements since joining in 2024.
Redefining Radiology Diagnosis
"In a small retrospective pilot performed for UTMB, Zauron was able to identify >20 patients with cardiac abnormalities or spinal fractures."
"Zauron found 529 patients with previously untreated abnormalities for UTHSA and identified the reimbursement mechanisms to cover all costs."
Zauron’s cutting edge technology passively generates databanks of radiology labels using biometric data collected from radiologists during standard of care assessments.
Missed Revenue Identified
Patients Impacted
Algorithms Available
