Method and system for implementing a generative machine learning architecture for contextual message generation

A method, comprising:

• storing, by one or more processors in a database, one or more text strings corresponding to an application feature and generated based on the use of the application feature by at least one entity;
• obtaining, by the one or more processors, one or more data files each comprising natural language content and generated based on a different communication interaction with a first entity;
• executing, by the one or more processors using a task agent, one or more large language models using the natural language content of the one or more data files to generate an identification of the application feature determined for the first entity;
• retrieving, by the one or more processors using the task agent, the one or more text strings corresponding to the application feature from the database using the identification of the application feature;
• filtering, by the one or more processors using the task agent, the one or more text strings based on at least one similarity between the first entity and at least one other entity associated with the one or more text strings;
• executing, by the one or more processors using the task agent, the one or more large language models using the filtered one or more text strings, the identification of the application feature, and an identification of the first entity as an input to generate a visual representation of the input;
• and
• transmitting, by the one or more processors, a message for presentation at a computing device of the first entity, the message containing the visual representation of the input.

A computing system, comprising:

• a network interface configured to communicate with at least one user device of a first entity;
• and
• at least one processing circuit coupled to the network interface, the at least one processing circuit comprising at least one processor and at least one memory, the at least one memory storing instructions therein that, when executed by the at least one processor, cause the at least one processor to:
• store, in a database, one or more text strings corresponding to an application feature and generated based on the use of the application feature by an entity;
• detect a termination of a communication session with at least one user device associated with a first entity;
• responsive to the detection, identify a recording or a transcript of the recording of the communication session with the at least one user device associated with the first entity, the recording or the transcript of the recording comprising natural language content;
• execute, using a task agent, one or more large language models using the natural language content of the recording or the transcript of the recording to generate an identification of the application feature determined for the first entity;
• retrieve, using the task agent, the one or more text strings corresponding to the application feature from the database using the identification of the application feature;
• filter, using the task agent, the one or more text strings based on at least one similarity between the first entity and at least one other entity associated with the one or more text strings;
• execute, using the task agent, the one or more large language models using the filtered one or more text strings, the identification of the application feature, and an identification of the first entity as input to generate a visual representation of the input;
• and
• transmit a message for presentation at a computing device, the message containing the visual representation of the input.