Abstract: Aspects of the disclosure relate to generating and providing enhanced user interfaces by implementing data, AI, intents and personalization (DAIP) technology. In some embodiments, a computing platform may receive, from enterprise computing infrastructure, first unstructured activity data associated with a first enterprise channel. Subsequently, the computing platform may identify one or more user intents by applying an intent discovery model to the first unstructured activity data associated with the first enterprise channel. Then, the computing platform may generate status tracking information based on identifying the one or more user intents.

Abstract: An entity may generate generic notifications for transmittal to a plurality of customers. One of the notifications may not be properly customized for a customer to whom the notification is scheduled for deployment. A system is provided that generates and refines generic notifications using artificial intelligence (“AI”). The system may include an application server running an AI engine for periodically monitoring, at a given point in time, historical customer data relating to less than a predetermined number of customers to ensure reduced, relative to a predetermined baseline, processing usage. The AI engine may determine, during the monitoring, that notifications transmitted by the platform to one of the customers have failed to elicit a positive response from the customer. The determination may prompt the AI engine to put the generic notification on hold for the customer and to perform additional steps to alter the generic notification to a targeted notification.

Abstract: An entity may generate generic notifications for transmittal to a plurality of customers. One of the notifications may not be properly customized for a customer to whom the notification is scheduled for deployment. A system is provided that generates and refines generic notifications using artificial intelligence (“AI”). The system may include an application server running an AI engine for periodically monitoring, at a given point in time, historical customer data relating to less than a predetermined number of customers to ensure reduced, relative to a predetermined baseline, processing usage. The AI engine may determine, during the monitoring, that notifications transmitted by the platform to one of the customers have failed to elicit a positive response from the customer. The determination may prompt the AI engine to put the generic notification on hold for the customer and to perform additional steps to alter the generic notification to a targeted notification.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for providing a propensity multiplier for customer message and opportunity management, such that an associate can more effectively assist a customer. The system may provide a customer profile associated with the customer to the channel. The profile compiles customer interaction data, including real-time and batched historic customer interaction data. This data is utilized to predict communication points and opportunities for the customer that may be most relevant to the customer. In this way, the system determines a propensity for each of the communication points and/or opportunities and modifies the ranking of each based on triggers from the received customer interaction data. Thus, providing the communication points and opportunities to an associate within a customer profile, such that the associate is prepared with communication points and opportunities tailored for the customer he/she is interacting with.