The development of visual AI systems for real-world applications is a complex undertaking characterized by a variety of diverse challenges. While the media spotlight is often focused on academic AI models that improve performance based on well-defined datasets, in many instances insufficient attention is dedicated to the engineering complexity of productizing real-world applications. In this presentation, we will begin with an overview of key topics that must be addressed in productizing complex visual AI systems, including the definition of system requirements; hardware and software design; data acquisition, labelling and management; and AI model development, deployment, validation and maintenance. Next, we’ll delve into software design and AI model deployment in greater detail. We’ll illustrate key challenges and promising techniques via practical examples and results from our work delivering visual AI systems for autonomous flight as part of Project Wayfinder at Acubed, Airbus’ innovation center in Silicon Valley.