Abstract: The present invention discloses a system and method for providing real time dynamic interface for supervising individuals. The system is configured to monitor a plurality of agent data of each agent or individual in real time. The system is configured to analyze the call data and generate a call data set. The system is configured to analyze the call data set and generate a plurality of problem profiles. The system is configured to analyze the problem profiles to determine a plurality of actions for each problem profile and generate a plurality of action profiles for each problem profile. The system is configured to select at least one problem profile, determine at least one action profile for the selected problem profile and enables the system to implement the actions in the action profile. The system is configured to provide supervisors with recommended actions and real time graphical user interface to quickly monitor and engage with agents.

Abstract: Methods and systems are disclosed herein for using machine learning models to predict proper resource levels and performance levels of those resources. One mechanism for predicting proper resource levels and performance levels of those resources may involve a use of a machine learning model that is enabled to receive user data as input and output a predication for one or more actions for each user. The users may be clustered based on the user action predicted by the machine learning model and one or more action sequences may be executed against each action cluster.