Product details

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Subject category: Entrepreneurship
Published by: Stanford Business School
Originally published in: 2021
Version: 22 March 2021
Revision date: 24-Nov-2021

Abstract

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.

Time period

The events covered by this case took place in 2021.

Geographical setting

Countries:
United States; Japan

About

Abstract

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.

Settings

Time period

The events covered by this case took place in 2021.

Geographical setting

Countries:
United States; Japan

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