Abstract: An AI Agent Platform autonomously processes data streams for event implementation. The AI Agent Platform receives a real-time data stream associated with a profile. The AI Agent Platform defines a dataset from the data stream by dynamically sampling the data stream according to a time window selected using the profile. The AI Agent Platform may detect a correspondence between the dataset and an event registry. The event registry may include proactive events having a predicted significance for a user. The AI Agent Platform may then execute a machine-learning model using an event, the dataset, and the profile to define an implementation of the event for the user. Upon receiving authorization to execute the event, the AI Agent Platform facilitates execution of the implementation of the event.

Abstract: Systems and methods for automatically and continuously processing communications exchanged among users and automated agents and corresponding user behaviors are provided to dynamically generate topical communications sessions from ongoing communications sessions. The topical communications sessions are implemented to reduce the cognitive effort of conversation management within existing communications sessions where topical drift may occur. The framework allows users to submit multimedia inputs that are classified by the systems and methods and automatically routed to appropriate communications containers.

Abstract: Systems and methods for automatically and continuously evaluating user data collected through different communications sessions and other data sources to perform user profiling and define familiar relationships amongst users.