US 12,086,586 B2
Artificial intelligence (AI) supported graph enabled method to manage upgrades for applications
Sakshi Bakshi, New Delhi (IN); Sathya Thamilarasan, Tamilnadu (IN); Shyamala Manoharan, Chennai (IN); Siva Kumar Paini, Telangana (IN); Sri Doraiswamy, Charlotte, NC (US); Srinivasa Dhanwada, Hyderabad (IN); and Nagalaxmi Sama, Telangana (IN)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Oct. 25, 2022, as Appl. No. 17/972,711.
Prior Publication US 2024/0134626 A1, Apr. 25, 2024
Prior Publication US 2024/0231794 A9, Jul. 11, 2024
Int. Cl. G06F 8/60 (2018.01); G06F 8/65 (2018.01); G06N 20/00 (2019.01)
CPC G06F 8/65 (2013.01) [G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computing platform comprising:
at least one processor;
a communication interface communicatively coupled to the at least one processor; and
memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:
train, based on historical information, an artificial intelligence (AI) engine, wherein training the AI engine configures the AI engine to identify, based on the historical information, application upgrade errors and corresponding actions to correct the errors;
receive, from a user device, a request to upgrade an application within an enterprise system;
create a simulated enterprise system, wherein the simulated enterprise system comprises system parameters that represent characteristics of the enterprise system and is modified by upgrading a copy of the application within the simulated enterprise system;
store the system parameters in a graphical database;
create virtual parameters that represent characteristics of the simulated enterprise system that was modified by the upgrading and correspond to the system parameters, wherein:
each virtual parameter that represents a characteristic of the simulated enterprise system corresponds to a system parameter that represents a corresponding characteristic of the enterprise system; and
differences between values of the virtual parameters and values of the corresponding system parameters represent differences between the characteristics of the simulated enterprise system and the corresponding characteristics of the enterprise system;
store, by modifying the graphical database, the virtual parameters with the system parameters;
detect, using the graphical database, at least one error, based on at least one difference between the system parameters and the corresponding virtual parameters;
input the at least one error, into the AI engine, wherein inputting the at least one error into the AI engine causes the AI engine to output at least one action to correct the at least one error;
execute the at least one action to correct the at least one error on the simulated enterprise system; and
send one or more commands directing the enterprise system to upgrade the application within the enterprise system and execute the at least one action to correct the at least one error on the enterprise system, wherein sending the one or more commands causes the enterprise system to upgrade the application within the enterprise system and execute the at least one action to correct the at least one error.