StopLift Checkout Vision Systems has developed software-based checkout vision systems which automatically analyze regular CCTV video from existing cameras to detect various forms of theft, training error, and operational analytics at the checkout. A pioneer in the field of checkout vision systems, StopLift has developed the first ever system capable of successfully detecting “sweethearting” between cashiers and customers (U.S. Patents 7,516,888 & 7,631,808). Rather than take a one-size-fits-all approach, StopLift has developed targeted applications to address the specific needs of retailers from different sectors, including general merchandise, grocery, and specialty retail. StopLift grew out of a Harvard Business School field study on Retail Loss Prevention entitled “Project StopLift”. One of the study’s major findings was that, while CCTV is the most widespread of all loss prevention technologies, it is often the most underutilized--it is just too expensive and time-consuming for humans to monitor or review video comprehensively. With engineering talent and computer vision research insights from MIT, the Project StopLift team realized that video recognition could be used to automate and, thus, make possible the comprehensive examination of surveillance video.