Amir Hever was driving into a government facility a few years ago when he discovered a huge flaw in their security process. As he approached the entrance gate, a security guard dropped to his knees to look underneath his vehicle. “When he stood up, I asked him what he was looking for,” said Hever, CEO and co-founder of computer vision startup UVeye. “The security guard answered honestly that he was looking for threats but actually couldn’t see anything.
That’s when I realized that something wasn’t working right.”
Hever assembled a team, and began researching the problem and potential solutions. Thus was born in 2016 UVeye, which has since built an under-vehicle inspection system that uses deep learning to bridge the security gap. Much of the New York-based company’s work centered on grasping the vast variety of vehicle undercarriages, not to mention the changes they undergo after thousands of miles on the road. What Hever and his team learned that it’s not easy to identifying anomalies in vehicle undercarriages.
