Patent ID: 11972215
Assignee: JPMORGAN CHASE BANK, N.A.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for providing automated support services by utilizing artificial intelligence, the method being implemented by at least one processor, the method comprising:
receiving, by the at least one processor via a graphical user interface, at least one request from a user, each of the at least one request including a request identifier;
compiling, by the at least one processor, operating state data when the at least one request is received, the operating state data representing a current state of a computing environment that is associated with the user;
performing, by the at least one processor using at least one model, a system check based on the compiled operating state data, the system check including a network check and a local machine check;
parsing, by the at least one processor using syntax analysis, the at least one request;
identifying, by the at least one processor from the parsed at least one request, at least one factor by using the at least one model,
wherein the at least one factor includes a request context that relates to a necessity of a component and a request sentiment that relates to a tone of the user;
wherein the at least one factor includes a score that is determined based on the request context and the request sentiment; and
wherein the score includes a user fear factor score;

associating, by the at least one processor, the at least one request with a category corresponding to the at least one factor, the category relating to a characteristic of the at least one request and includes an urgent issue category;
determining, by the at least one processor using the at least one model, whether the at least one request can be automatically resolved based on the at least one factor and the category;
initiating, by the at least one processor, at least one action based on a result of the determining;
tracking, by the at least one processor, quantitative feedback and qualitative feedback for each of the at least one request by using the corresponding request identifier;
training, by the at least one processor, the at least one model by using additional data, the additional data including the tracked quantitative feedback and the tracked qualitative feedback; and
assessing, by the at least one processor, the trained at least one model to determine whether at least one error rate is within a predetermined range.