AI Engine for Automated Error Resolution in Call Centers
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Solution Overview
Problem
Current error resolution processes in call centers and interactive voice response systems are time-consuming and inefficient, as human representatives may not be able to identify and address all errors experienced by customers across an enterprise, leading to processing delays and poor customer satisfaction.
Innovation Solution
A computing platform with an artificial intelligence engine that trains on historical error and solution data to automatically identify and resolve errors for users, providing solutions and performing corrective actions, while also allowing for human intervention when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human representatives manually resolve errors in call centers, then customer service can be provided, but processing time increases and productivity decreases
Solution Approach 1:
The system enables self-service error resolution by automatically detecting errors, generating solutions, and executing corrective actions without requiring human agent intervention. The AI engine processes errors independently, allowing customers to receive immediate assistance without waiting for call center availability.
Solution Approach 2:
The patent replaces the mechanical manual processing system with an automated AI-based system. The AI engine substitutes human cognitive processes for error detection, analysis, and resolution, enabling faster and more consistent error handling through algorithmic processing rather than manual intervention.
2Productivity
If human agents manually identify and solve errors, then errors can be resolved, but the scale of error resolution is limited by human capacity
Solution Approach 1:
The AI engine provides universal error resolution capability by being trained on diverse error types and solutions. It can handle multiple error categories (authentication errors, transaction errors, system errors) simultaneously, making the system scalable and adaptable to various error scenarios without requiring specialized agents for each error type.
Solution Approach 2:
The system changes the operational parameters from human-based to machine-based processing. The AI engine processes errors at machine speed and can simultaneously analyze multiple error types, transforming the resolution capacity from limited human bandwidth to unlimited computational capacity.
3Reliability
If comprehensive error monitoring is implemented, then all errors can be detected, but system complexity increases
Solution Approach 1:
The AI engine serves as an intermediary layer between error detection and resolution. It receives raw error data, processes it through trained models, and generates appropriate solutions. This intermediary approach simplifies the overall system by centralizing error processing logic rather than requiring complex distributed monitoring and resolution systems.
Solution Approach 2:
The system implements feedback mechanisms where the AI engine learns from resolved errors and updates its models. This feedback loop enables continuous improvement of error detection accuracy without requiring increasingly complex monitoring systems, as the AI adapts to new error patterns through training data rather than system complexity increases.
Data Source
AI summary
Aspects of the disclosure relate to automated error processing. A computing platform may receive historical error/solution information. The computing platform may train, using the historical error/solution information, an artificial intelligence engine to automatically identify solutions for current errors for a plurality of users. The computing platform may identify current errors for a user of the plurality of users. The computing platform may notify the user of the current errors. The computing platform may receive a request to correct an error of the one or more current errors. The computing platform may identify, using the artificial intelligence engine, a solution to the error. The computing platform may automatically perform actions to achieve the solution. The computing platform may send, after performing the actions, commands directing an event processing system to process an event with which the error was associated, which may cause the event processing system to process the event.