Abstract: Embodiments relate to web applications and interfaces providing personalized access to relevant wellness resources using microservices and machine learning models. Embodiments relate to web applications and interfaces that provide recommendations based on personas computed using machine learning models. The interfaces and web applications using microservices to provide interface tools that scale to multiple users.

Abstract: A method for generating a user profile based on a comparison to peer group data, the user being a member of an institution, the method comprising the steps of: obtaining user profile data pertaining to a user of a network service of the institution; accessing group profile data associated with the user; comparing the user profile data to the group profile data to generate comparative data; generating a user profile for presentation on a user interface, the user profile including the comparative data; sending the user profile to the user; receiving a request from the user for a product of institution; and updating the user profile to include information pertaining to the product.

Abstract: A system receives data associated with a communication between one or more individuals. The data is split between each of the one or more individuals into text associated with that individual. Each of the text is modified to remove stop words and to duplicate key words. The text is merged to form a text corpus, from which a bag of words model is generated. Topics of the bag of words are classified using a topic classifier model. A purpose is identified based on the returned topic and keywords from the topic classifier model. Returned topics and keywords from the topic classifier model are linked to the communication.

Abstract: A system receives data associated with a communication between one or more individuals. The data is split between each of the one or more individuals into text associated with that individual. Each of the text is modified to remove stop words and to duplicate key words. The text is merged to form a text corpus, from which a bag of words model is generated. Topics of the bag of words are classified using a topic classifier model. A purpose is identified based on the returned topic and keywords from the topic classifier model. Returned topics and keywords from the topic classifier model are linked to the communication.