DeepBoxes are multi-purpose and can be used for applications such as defect detection in quality control and threat recognition in security. They are optimized for real-time processing of visual data with AI and adapt to a wide variety of use cases. The architectures make them ideal for either open or closed-loop deployments (where internet access is not permitted). Another benefit is cost control, where running AI algorithms on device is used to avoid going over budget in terms of compute and energy costs.