Individualized channel error detection and resolution
Abstract:
Aspects of the disclosure relate to using natural language processing to identify a context of failure associated with a channel error and analyzing the identified context of failure in relation to historic data by machine learning algorithms to identify one or more of a severity ranking, alternate channel, and solution for the channel error. In some instances, a computing platform may receive data corresponding to a system event associated with a channel of server infrastructure, identify a technical issue, customer intent, and customer sentiment of the system event, determine a context of failure of the system event, generate a mapping of the context of failure in relation to historic data, and identify a suggested solution, severity assignment, and alternate channel for the system event based on the mapping of the context of failure in relation to the historic data.
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