Igel provides a command-line interface for machine learning workflows, allowing users to train, evaluate, and use models through configuration files rather than code. It wraps scikit-learn and other ML libraries under the hood, supporting common algorithms, preprocessing, and AutoML capabilities. Users define model parameters and data paths in YAML, JSON, or via CLI arguments, and the tool handles the rest.