Real-time Agent Assist System for Crisis Knowledge Verification
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Solution Overview
Problem
Contact centers face challenges in handling crisis situations due to the lack of foreknowledge about the crisis, making it difficult for artificial intelligence systems to verify customer input and provide accurate responses, as the information is dynamic and often unverified.
Innovation Solution
A system that includes a processor and memory with a crisis knowledge base, which is created ad hoc in response to a crisis scenario, allowing for real-time agent assist by evaluating information requests using natural language understanding to determine confidence, veracity, frequency, and proximity of knowledge fragments, and generating responses based on these analyses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If artificial intelligence systems are trained over extended periods to assist contact center agents, then the system can handle routine inquiries effectively, but the system cannot handle crisis situations due to lack of foreknowledge
Solution Approach 1:
The system dynamically adapts its knowledge base during crisis situations by continuously ingesting new information from multiple sources, allowing it to transition from static pre-trained knowledge to dynamic real-time knowledge acquisition and verification
Solution Approach 2:
The system performs preliminary verification of information sources and establishes trust relationships before crisis events occur, enabling faster and more reliable information processing when crises happen
2Speed
If the system accepts customer input during crises, then it can provide timely responses, but the input cannot be easily verified for accuracy
Solution Approach 1:
The system introduces intermediary verification mechanisms including multiple information sources, confidence scoring systems, and cross-validation processes that act as mediators between customer input and final response generation
Solution Approach 2:
The system implements feedback loops where information is continuously verified against multiple sources, with confidence scores adjusted based on verification results, enabling rapid iteration and improvement of information accuracy
3Stability of the object's composition
If the system uses a traditional knowledge base, then it can provide consistent responses, but it cannot normalize dynamic crisis information from multiple sources
Solution Approach 1:
The system changes key parameters including confidence scores, source reliability weights, and information freshness metrics to dynamically adjust how crisis information is processed and normalized while maintaining response consistency
Solution Approach 2:
The system creates a composite knowledge structure that integrates pre-trained AI knowledge, real-time crisis information from multiple sources, and verification results into a unified normalized format that maintains both consistency and adaptability
Data Source
AI summary
A system for real-time agent assist in a crisis scenario according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to receive an information request from a contact center client, evaluate the information request using natural language understanding to determine a knowledge fragment associated with the information request, analyze the knowledge fragment based on a crisis knowledge base of the system with respect to at least one of a confidence in the knowledge fragment, a veracity of the knowledge fragment, a frequency of the knowledge fragment, or a proximity of the knowledge fragment to the crisis scenario, and generate a response to the contact center client in response to analysis of the knowledge fragment based on the crisis knowledge base.