The collaboration between a Humanities scholar and an AI engineer has yielded an innovative AI toolkit and start-up known as The Möbius Trip Replay. This multimodal deep-learning toolkit automatically manages extensive data from movies and TV shows, facilitating digital analysis of cultural representation. Positioned at the confluence of digital humanities, intercultural communication studies, film and television studies, multimodality, and AI, our research aims to contribute to academia, computer science, the film industry, and broader user communities. This paper outlines the entrepreneurial journey from conception to realization, highlighting the diverse intended users and potential impacts. Theoretical frameworks drawn from film theories, intercultural communication models, and multimodality inform our approach. We detail methodologies including cultural analytics, reverse-engineering, and distant reading, as well as an inventory of predecessor tools like Cinemetrics and ImageJ Multimodal Analysis software. Central to our discussion is The Möbius Trip Replay, elucidating its features, underlying technology (Google Cloud Platform, model training), and concept of blueprints (genre, culture, time period, etc.). Additionally, we present early findings from specific case studies, offering a comprehensive exploration of the theories, methodologies, and tools underpinning our AI toolkit and start-up venture.