Abstract: A computing system for AI-based database configuration, includes: at least one processor; a communication interface communicatively coupled to the at least one processor; and a memory device storing executable code that, when executed, causes the at least one processor to: access a database containing historical data; access data containing one or more target values; deploy a trained AI program to generate a plurality of action paths based on the historical data; use the AI program to predict a probability of meeting the target value for each action path; select one of the action paths having the highest probability; store the selected action path in the database; receive an error signal representing a difference between the target value and an actual achieved value; update the historical data based on the error signal; and retrain the AI program using the updated historical data.

Abstract: A system and method for parsing data structure ontologies in a database environment to identify, organize and index data files include: a processor; a non-transitory memory operably connected to the processor; and a targeted actions application stored in the memory and including executable instructions that, when executed by the processor, cause the processor to: identify and organize data associated with a user, the data being stored in a users database in the memory; identify rules associated with the user stored in a rules database in the memory; use artificial intelligence machine learning to analyze the data and detect patterns in the data; apply the rules to the detected patterns to generate targeted actions; assign ranks to the targeted actions and select a one of the targeted actions having a highest rank; generate a message including the selected targeted action; and send the message to a user device of the user.