The library enables data scientists to understand how their models make predictions by generating clear, labeled visualizations. It supports both local explanations (individual predictions) and global explanations (overall model behavior) through integration with SHAP and LIME. Users can deploy an interactive webapp to share model insights with both technical and non-technical stakeholders.