Metahuman Concierge Platform for Empathetic Customer Service
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Solution Overview
Problem
Traditional customer service models, both human-centric and digital, face challenges such as inconsistent information, ineffective communication, and lack of empathy, leading to customer dissatisfaction and increased operational costs. Additionally, existing digital solutions often struggle to provide flexible and adaptable customer interactions.
Innovation Solution
A metahuman concierge platform utilizing conversational generative AI, which includes a microservice layer with a voice module, conversation module, avatar module, and business logic module, to provide personalized and flexible customer engagement through voice, video, or text interactions across various interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional digital solutions (chatbots, IVRs) are used for customer service, then operational costs are reduced and immediate responses are provided, but customer satisfaction deteriorates due to inconsistent information, ineffective communication, and lack of empathy
Solution Approach 1:
The patent creates a metahuman concierge that copies human appearance, behavior, and communication patterns. The metahuman is rendered photorealistically with human-like facial expressions, body language, and conversational abilities, allowing customers to interact with a digital entity that mimics human empathy and understanding while maintaining the efficiency of automated service.
Solution Approach 2:
The system transforms traditional digital chatbot parameters by integrating generative AI models that enable dynamic, context-aware responses. The metahuman's communication parameters include natural language processing, emotional tone detection, and adaptive conversation flow, moving from rigid script-based interactions to flexible, human-like dialogues that maintain both efficiency and satisfaction.
2Reliability
If human customer service representatives are used, then customer satisfaction improves through empathy and understanding, but operational costs increase and response time extends due to training requirements and human limitations
Solution Approach 1:
The metahuman concierge replicates human empathetic communication capabilities through AI models trained on human interaction patterns. It displays human-like facial expressions, maintains appropriate eye contact, uses natural body language, and demonstrates emotional intelligence in conversations, providing the satisfaction benefits of human service without the associated costs and limitations.
Solution Approach 2:
The patent replaces the mechanical system of human employees with a digital metahuman system. This substitution eliminates costs related to hiring, training, retaining, and managing human workers while maintaining or enhancing service quality. The metahuman operates continuously without fatigue, provides consistent responses, and scales efficiently to handle multiple customers simultaneously.
3Speed
If traditional digital engagement systems are used, then immediate responses are provided, but adaptability deteriorates due to predefined decision trees and inability to handle complex or unexpected queries
Solution Approach 1:
The system changes the fundamental parameters of digital response systems by integrating generative AI models that can dynamically generate appropriate responses to novel situations. Instead of following predefined decision trees, the metahuman uses natural language processing and contextual understanding to adapt to unexpected queries, maintaining both rapid response times and high adaptability.
Solution Approach 2:
The metahuman incorporates real-time feedback mechanisms that allow it to learn from and adapt to customer responses during interactions. The system analyzes customer emotions, adjusts its communication style accordingly, and continuously improves its responses based on interaction outcomes, enabling both speed and adaptability in customer service.
Data Source
AI summary
The invention provides a method for delivering customer engagement through a metahuman concierge platform. The method includes an interface for interaction, a database layer for application data and a controller for the metahuman concierge platform. The controller includes a microservice layer with a voice module, a conversation module, an avatar module and a business logic module. The system displays a conversational agent for voice, video, or text interaction. The interface can be a mobile app, a kiosk, a web app, or a holograph. The microservice layer can include a rest API. The conversation module controls textual responses through generative large language models, and the voice module provides text to voice generation. The avatar module provides meta human features, and the business logic module incorporates functional logic for the processes.