FEDOT provides automated generative design of machine learning pipelines for various real-world problems. The framework uses evolutionary approaches to optimize pipeline structures and hyperparameters, supporting binary and multiclass classification, regression, clustering, and time series prediction tasks. Pipelines are represented as graphs defining connections between data preprocessing and model blocks, with the system managing complex interactions between these components.