Data-driven tools have been developed to support workflows and decision-making. Most of these tools are trained with large studio production examples, and their AI also caters to large studios. Snowflake aims to support independent artists and student media-makers, who have fundamentally different needs. Optimizing box office revenue or script conformity to formula writing is not the interest of indie, art, and student media-makers – instead, they take risks to explore new forms of storytelling and keep evolving the medium. As a data-driven solution for creative media-making, Snowflake is predominantly a search and analysis tool, rather than a prediction or optimization tool. Decision-making is not handed to AI, but stays in the hands of the creative human; AI supports creators to make informed and inspired decisions.  Snowflake uses a hybrid approach, combining machine-learning and AI for search, image analysis, and scene comparison through a rich and evolving database with creative methods and examples.

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