Techniques for automated self-adjusting corporation-wide feature discovery and integration

This invention describes a system that automatically prepares a client's data for use with a machine learning model. It works by reviewing the client's data, understanding how it's organized, and then mapping that organization to what the machine learning model expects. For each specific client problem, the system automatically identifies and ranks the most important data points (features) by testing their influence on the model's results. It then creates and updates a weighted list of these features, making the machine learning solution adaptable to different clients without needing manual adjustments.