Saul is a declarative learning-based programming framework developed by the Illinois Cognitive Computation Group. It focuses on enabling users to create machine learning models using a high-level, declarative approach, which simplifies the process of model development and experimentation. The framework is designed to facilitate the integration of various machine learning techniques and provides tools for efficient data handling, model training, and evaluation. Saul is particularly aimed at researchers and developers looking to leverage cognitive computing methods in their projects.