A retail company wants to forecast weekly product demand across 5,000 store-item combinations. The dataset includes historical sales, promotional flags, holiday calendars, and price changes. The team needs a single model that can produce probabilistic forecasts (with prediction intervals) for all series simultaneously and learn shared patterns across related items. Which SageMaker built-in algorithm best fits this requirement?