Bank of America Corporation

Venugopal Purushothaman

Lakshmanan Palaniappan

Virgil Arputharaj

Chandan Yadu Varaha Vedagiri

Embodiments of the present invention are directed to a cognitive tracking and navigation training system for improved application performance. Embodiments of the invention are configured to operate on complex enterprise application systems where a plurality of navigation paths are available to users based on one or more assigned user roles. The present system provides an enhanced application performance by cognitively tracking and providing updated user navigation paths while a user accesses an enterprise application system.

Cognitive tracking and navigation training system for improved application performance

Disclosed is a system for automated archival and synchronization that includes a processor and a memory, wherein archival, partition, and synchronization applications are stored in the memory. The system is typically configured for: identifying triggering of an event and establishing a communication link between a source system and a destination system, determining that the event meets archival criteria and initiating archival process, wherein the archival process comprises determining that a first configuration of the source system does not match the second configuration of the destination system and synchronizing the second configuration with the first configuration, migrating a first set of data from the source system to update a second set of data in the destination system based on determining a change in the first set of data, and compressing the updated second set of data in the destination system.

Automated archival partitioning and synchronization on heterogeneous data systems

A computing platform may receive a primary model corresponding to one or more features of an application. The computing platform may populate, using a processing engine and based on the primary model, a secondary model indicating an object definition corresponding to the one or more features. The computing platform may generate, using a pre-deployment engine and based on the primary model, a script corresponding to the one or more features. The computing platform may generate one or more commands directing a production server to execute, in a production environment, the script corresponding to the one or more features. The computing platform may transmit, to the production server and via the communication interface, the one or more commands directing the production server to execute the script. The computing platform may receive, based on the one or more commands, an error corresponding to the one or more features.

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Tamil Nadu, India

Venugopal Purushothaman