QAS.AI's innovative approach to enhancing aneurysm surgery through artificial intelligence has been highlighted in a recent article by WNY Papers. The piece discusses our collaborative efforts with the University at Buffalo to develop AI-driven tools that assist neurosurgeons in predicting the success of aneurysm treatments. By analyzing angiographic imaging data, our technology aims to provide real-time insights during procedures, potentially improving patient outcomes and surgical precision.​

QAS.AI has received a research and development grant from the University at Buffalo's Center for Advanced Technology in Big Data and Health Sciences (UB CAT). This funding supports our ongoing collaboration with UB neurosurgery faculty to enhance our AI platform's capabilities in predicting aneurysm healing during neuroendovascular procedures. The grant facilitates the refinement of our algorithms and the expansion of clinical validation efforts, aiming to improve patient outcomes through real-time, data-driven decision support.​

We’re excited to share that QAS.AI has received a $1 million Phase II grant from the National Science Foundation (NSF) through the Small Business Technology Transfer (STTR) program. This award will support the development of our AI-powered platform for real-time, intraoperative prognosis of aneurysm occlusion. The project moves beyond prototype, enabling clinical-grade software development and multi-site evaluation in collaboration with Gates Vascular Institute, Mercy Hospital of Buffalo, and the University of South Florida. Our goal: empower clinicians with automated occlusion probability insights during neuroendovascular procedures, reducing the need for follow-up interventions and enhancing patient outcomes.

We’re thrilled to announce the launch of our interactive software demo, developed in collaboration with Morhead Design, showcasing QAS.AI’s real-time AI guidance for neuroendovascular procedures.This milestone marks the transition from prototype to clinical deployment—with our system now live and actively undergoing testing at Gates Vascular Institute, a nationally recognized center for cerebrovascular innovation.The demo highlights QAS.AI’s ability to: Automatically detect aneurysms and injection inlets Analyze contrast dynamics from angiographic sequences Provide probability-based predictions for aneurysm occlusion at 6 months Deliver results in under 1 second, directly in the angio suite This clinical integration represents a key step toward translating our NSF- and UB CAT-supported research into a standard-of-care decision support tool.

QAS.AI has been spotlighted by the University at Buffalo's Jacobs School of Medicine and Biomedical Sciences for its innovative AI-driven software designed to assist neurosurgeons during procedures. The software analyzes live angiographic imaging to estimate the probability of successful aneurysm occlusion, providing real-time data to inform surgical decisions. Developed from research in Dr. Ciprian Ionita’s lab, the technology has secured a patent application and received $256,000 from the NSF's Small Business Technology Transfer program to support its development.