Focal Systems, with fresh new Series B funding and more new orders than it could handle, believed its novel out-of-stock detection system would prove the sweet spot in the automation of traditional brick and mortar retail stores. Small cameras on store shelves could automatically log any products in need of resupply, but also order the items to restock, saving store managers valuable time each day. Stores would see lower labor costs but also would benefit from a more efficient resupply system. The competition for automation in retail was stiff, and becoming more intense. How could Focal convince retailers to give its innovative technology a try-and could the company fend off the competition?

Could AI-based X-ray scanning platform make flying safer? Airport security officers had just seconds to decide if someone's luggage contained a knife, gun, explosive, or other potential safety threat, and the human eye was not designed to focus for hours on a scanning screen. This case study describes the founding and early years of Synapse Technology, which aimed to improve airport security performance by leveraging advances in computer vision to detect these types of threats with far greater accuracy. The company set out to develop the AI solution they believed would work, building an AI model and then feeding it training data on which types of weapons and other items to flag as a threat, as passengers' luggage went through the screening process. The case study explores the technical as well as entrepreneurial challenges in this new AI frontier, including locating a real-world test venue, and then determining how to measure and explain the return on investment to potential clients.