Modal partnered with a top soccer team, AFC Richmond, to help them process and analyze large amounts of tracking data from matches. The current system was not well-suited for this task due to limitations in scalability and cost-effectiveness. Modal's serverless batch processing on GPUs provided a flexible infrastructure that reduced costs by 50% and enabled the team to scale automatically based on data volume. The partnership also led to the development of a lightweight in-memory vector DB, allowing the coaching staff to make queries based on semantic similarity of embeddings generated during analysis. This solution enables AFC Richmond to gain valuable insights into player performance and make informed decisions for future matches.