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

Claim 10:
11. A computing device configured to implement an execution of a method for providing automated support services by utilizing artificial intelligence, the computing device comprising:
a processor;
a memory; and
a communication interface coupled to each of the processor and the memory,
wherein the processor is configured to:
receive, via a graphical user interface, at least one request from a user, each of the at least one request including a request identifier;
compile 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;
perform, by 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;
parse, by using syntax analysis, the at least one request;
identify, 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;

associate 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;
determine, by 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;
initiate at least one action based on a result of the determination;
track quantitative feedback and qualitative feedback for each of the at least one request by using the corresponding request identifier;
train the at least one model by using additional data, the additional data including the tracked quantitative feedback and the tracked qualitative feedback; and
assess the trained at least one model to determine whether at least one error rate is within a predetermined range.