Flash floods are a significant global hazard, causing numerous fatalities annually, making them incredibly dangerous. Early warning systems are crucial for minimizing flood damage and saving lives. A "warning gap" exists where many developing nations lack effective early warning systems. The text introduces new AI-powered flash flood forecasts for urban areas, predicting risks up to 24 hours in advance. This initiative builds upon existing riverine flood forecasting models, addressing the unique challenges of rapid-onset flash floods. A major challenge is the lack of readily available data for flash flood events. The new model leverages a novel AI-powered methodology called Groundsource to create a dataset of past events. The model utilizes global weather data and forecasts, offering broader reach. The developed model focuses on urban areas, covering the majority of the world's population. Evaluation reveals strong accuracy, especially in areas often lacking traditional forecasting. The initiative aims to enhance climate resilience by providing crucial information for safety in a changing climate.