AI Ticket Resolution Using NLP and Automated Triage
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Solution Overview
Problem
Conventional systems require significant manual assessment by service providers to resolve customer issues, leading to inefficiencies and customer frustration due to the difficulty in navigating service provider resources for solutions.
Innovation Solution
A computer-implemented system using natural language processing and AI to analyze user-provided issue descriptions, autonomously determine resolvability, extract necessary information, and either resolve the issue directly or assign it to a work group, providing job aids or estimated resolution times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual assessment is used to resolve customer issues, then service providers can accurately understand and address customer problems, but the process requires significant labor hours and electronic resources
Solution Approach 1:
The system enables self-service by using NLP to automatically analyze customer issue descriptions, extract relevant information, and resolve issues without requiring manual assessment by service providers. The system autonomously processes tickets by comparing extracted information against known issue patterns and resolutions in the database, thereby eliminating the need for human labor while maintaining accurate problem understanding and resolution.
2Adaptability or versatility
If service providers provide comprehensive service manuals and job aids, then customers can find solutions independently, but customers find it difficult to navigate these resources and are more likely to open tickets
Solution Approach 1:
The NLP-based system acts as an intermediary between customers and the comprehensive knowledge base. Instead of requiring customers to manually navigate through extensive manuals and job aids, the system automatically analyzes the customer's issue description, extracts key parameters, and retrieves the most relevant solutions from the database. This intermediary process transforms the complex navigation task into an automated information retrieval process, making solutions easily accessible without requiring customer effort to browse or search through resources.
3Productivity
If automated systems are used to resolve issues, then manual labor and electronic resources are reduced, but the system must accurately analyze natural language and determine resolvability conditions
Solution Approach 1:
The automated analysis system is segmented into distinct functional modules: an NLP module that analyzes natural language input and extracts parameters, a resolution determination module that compares extracted parameters against resolvability conditions in the database, and a solution retrieval module that fetches appropriate resolutions. This segmentation allows each component to perform its specific function with optimized complexity, rather than requiring a single monolithic system to handle all aspects of analysis and resolution, thereby managing overall system complexity while maintaining high automation efficiency.
Data Source
AI summary
Some aspects of the present disclosure are directed to computer-implemented systems and methods for efficient ticket resolution. The methods may include: receiving a request to resolve an issue; analyzing, via natural language processing, the language in the request to determine the issue to be resolved; determining whether the issue meets a condition for automated resolution; if the condition is met: extracting, via an application programming interface and from the at least one user device, information needed to resolve the issue; and resolving the issue using the extracted information; and if the condition is not met: generating a ticket; assigning a work group to the ticket; determining whether a job aid associated with the issue exists; and forwarding at least one of: the job aid; received communications from the work group; and an estimated amount of time to resolution.