The solution helps users interpret complex black-box machine learning models by bringing out the important features which the model uses for predictions. It also identifies the features and their effect on the predictions, for each of the predictions. The solution supports 40+ tree based classifiers and regressors such as Random Forest, Decision Trees, XgBoost, CatBoost etc.