Systems and methods for distributing network application data according to machine-learning output

A method, comprising:

• receiving, by one or more processors coupled to non-transitory memory, from an application executing on the client device, during a communication session, a first prompt for a language model comprising a request for information corresponding to the application;
• identifying, by the one or more processors, using the first prompt, an identifier of a first application interface of the plurality of application interfaces of the application to satisfy the request for information;
• generating, by the one or more processors, using the language model, the first prompt, and the identifier, output comprising a data structure corresponding to formatting of a graphical element that, when interacted with, causes navigation to the first application interface;
• providing, by the one or more processors, the output to the client device in response to the request, causing the client device to parse the data structure and generate the graphical element for display in a graphical user interface;
• receiving, by the one or more processors, from the client device, a second prompt indicating a request to update the at least one wager recommendation;
• generating, by the one or more processors, using the language model, the second prompt, and the data structure, second output comprising a second data structure corresponding to formatting of a second graphical element for the at least one wager recommendation;
• and
• providing, by the one or more processors, the second output to the client device, causing the client device to parse the second data structure and generate the second graphical element for display in the graphical user interface.