Digital Twin Agent for IVRS Call Navigation
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Solution Overview
Problem
Existing IVRS systems face challenges such as complex menu options, inability to rejoin calls after disconnection, and slowness in reaching desired destinations, often requiring users to navigate through numerous menus to reach a live human, and fail to consider the context of current calls when using captured user options in future interactions.
Innovation Solution
A system that creates a digital twin agent based on user characteristics and historical IVRS dialog data, allowing it to dynamically initiate and interact with IVRS systems, seamlessly switching between the digital twin agent and the user when human intervention is required, and providing context-aware navigation through IVRS menus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional IVRS systems use automated menu options to route calls, then call allocation efficiency is improved, but the system fails to consider context of current calls and requires users to navigate through numerous menus
Solution Approach 1:
The patent creates a digital twin agent that copies the user's characteristics, preferences, and historical interaction patterns. This digital twin autonomously navigates the IVRS menu system on behalf of the user, eliminating the need for users to manually navigate through complex menus while maintaining context-aware routing decisions based on the copied user profile and historical data.
2Extent of automation
If IVRS systems capture user options for future interactions, then automation is improved, but the system cannot adapt to changed context in current calls
Solution Approach 1:
The digital twin agent dynamically adapts to changed contexts by continuously analyzing current call circumstances and comparing them with historical interaction patterns. The system updates the digital twin's understanding of user preferences and situational context in real-time, allowing automated decision-making that remains flexible and responsive to changing conditions rather than relying on static captured options.
Solution Approach 2:
The system implements feedback loops where the digital twin agent's interactions with the IVRS system are continuously monitored and analyzed. Historical data from these interactions feeds back into updating the digital twin's model of user preferences and behavior patterns, enabling the system to learn and adapt to evolving contexts while maintaining high automation levels.
3Reliability
If users manually navigate IVRS menus to reach live humans, then call routing accuracy is improved, but time to reach destination increases significantly
Solution Approach 1:
The digital twin agent serves as an intermediary between the user and the IVRS system. It autonomously performs the menu navigation tasks that would otherwise require manual user interaction, using the user's historical preferences and contextual information to make intelligent routing decisions. This intermediary approach maintains accurate call routing while eliminating the time users would spend manually navigating menus.
4Device complexity
If IVRS systems operate with fixed automated responses, then system simplicity is improved, but ability to handle occupied users decreases
Solution Approach 1:
The digital twin agent enables self-service functionality where the system automatically handles call routing and menu navigation without requiring active user participation. When users are occupied or unavailable, the digital twin autonomously interacts with the IVRS system on their behalf, making decisions based on the user's historical behavior patterns and current context, thereby maintaining system simplicity while significantly improving adaptability to user availability.
Data Source
AI summary
An embodiment for simulating an interactive voice response system (IVRS) call with a digital twin agent of a user is provided. The embodiment may include receiving data relating to characteristics of the user, activities of the user, and historical data relating to one or more prior IVRS dialogs. The embodiment may also include creating a digital twin agent of the user. The embodiment may further include identifying one or more preferences of the user from the historical data. The embodiment may also include in response to determining the user is occupied, identifying a context of an issue requiring an IVRS call. The embodiment may further include initiating the IVRS call with the digital twin agent representing the user. The embodiment may also include transcribing an IVRS script and interacting with the IVRS in accordance with the IVRS script and the one or more preferences of the user.