Abstract: Techniques for applying predictive analytics to usage data in an event-driven architecture comprise systems, methods and storage mediums. A system having an event-driven architecture that facilitates proactive engagement with a customer over a network may comprise a memory storing instructions, a data storage that stores prompt data of one or more customer actions, and one or more processors. The one or more processors may execute the instructions to receive customer input data from the customer, provide the customer input data to a streaming inference engine that identifies one or more customer usage patterns, generate a customer servicing model based on the one or more customer usage patterns and the prompt data, store the customer servicing model in the data storage, provide an output to the customer based on the customer servicing model, and continuously update the customer servicing model stored in the data storage.

Abstract: Techniques for providing an immersive simulation of an itinerary comprise systems, methods and storage mediums. A system for providing an immersive simulation of an itinerary may comprise memory storing instructions and one or more processors communicatively coupled to a network. The one or more processors may be configured to execute the instructions to: acquire historical transaction data of a financial account, provide the historical transaction data to an enterprise AI platform to generate one or more personalized recommendations for the itinerary based on the historical transaction data, receive triggering data indicating a transaction of the financial account for a product and/or service, generate the immersive simulation including the one or more personalized recommendations, generate a link to the immersive simulation that is executable by a device, and provide at least one package over the network.