System and method for developing an artificial specific intelligence (asi) interface for a specific software

A computer-implemented method for developing an artificial specific intelligence (ASI) interface for specific software, the computer-implemented method comprising:

• identifying, by one or more hardware processors, a specific software package and a user base for generating an artificial specific intelligence (ASI) interface;
• generating, by the one or more hardware processors, an interaction model for the identified specific software package based on a medium of interaction with a user;
• generating, by the one or more hardware processors, an initial version of the ASI interface comprising the generated interaction model;
• deploying, by the one or more hardware processors, the generated initial version of the ASI interface with a subset of the user base;
• periodically obtaining, by the one or more hardware processors, interaction data between the ASI interface and the user;
• identifying, by the one or more hardware processors, interaction patterns and pre-defined issues associated with the user by analyzing the obtained interaction data;
• training, by the one or more hardware processors, a machine learning model based on the identified interaction patterns and the pre-defined issues associated with the user;
• and
• optimizing, by the one or more hardware processors, the initial version of the ASI interface based on the trained machine learning model.

The computer-implemented method of claim 19 further comprising:

• pre-processing, by the one or more hardware processors, the unstructured text data obtained from letters of reference extracted from the user base;
• generating, by the one or more hardware processors, machine-learning-based summaries of the pre-processed unstructured text data using at least one of an AI-based summarization algorithm, a transformer encoder-encoder machine learning model with a bidirectional encoder and an autoregressive decoder;
• validating, by the one or more hardware processors, the generated machine-learning-based summaries based on one or more predefined rules;
• and
• mapping, by the one or more hardware processors, text with the model variables to generate a long form structured text data desired by the user.

A non-transitory computer-readable storage medium having programmable instructions stored therein, that when executed by one or more hardware processors, cause the one or more hardware processors to:

• identify a specific software package and a user base for generating an artificial specific intelligence (ASI) interface;
• generate an interaction model for the identified specific software package based on a medium of interaction with a user;
• generate an initial version of the ASI interface comprising the generated interaction model;
• deploy the generated initial version of the ASI interface with a subset of the user base;
• periodically obtain interaction data between the ASI interface and the user;
• identify interaction patterns and pre-defined issues associated with the user by analyzing the obtained interaction data;
• train a machine learning model based on the identified interaction patterns and the pre-defined issues associated with the user, and
• optimize the initial version of the ASI interface based on the trained machine learning model.