AUTOMATION FOR WORKFLOW EMULATION FROM RECORDED WORK SESSIONS USING MICROSERVICE NETWORK

Abstract: recorded sessions of skilled personnel at work are used to train a first machine learning (ml) tool to extract workflow maps. these maps are used to train a second ml tool to emulate at least one workflow. the first ml tool is trained to predict an annotator's output. either ml tool can be a copilot having a microservice network architecture. further, complex sets of workflows can be subdivided for efficient support with small ml tools for (1) workflow map extraction and (2) emulation. based on segment demarcation accompanying a recording, segments are assigned to specialized ml extraction tools for workflow map extraction. extracted workflow maps are used to train workflow emulator(s). similarly, specialized ml emulation tools can emulate respective tasks. a distribution microservice can identify a task to be emulated and can invoke the appropriate specialized ml tool. similar microservice network architectures support both applications.

Inventor(s): Elaine Kelsey, Sazzad Mahmud Nasir, Jeffrey Thomas Yarbro, Lauren Elizabeth Egerton, Elliot Nicholas Robson, Brendan Michael Kelly, Robert Oscar Robson, Spencer Thomas Ward

CPC Classification: G06F9/5027 (Allocation of resources, e.g. of the central processing unit [CPU])

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