Telephony-to-AI Chat Handoffs Using Authentication and Intent Tokens
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Solution Overview
Problem
Existing customer service systems face inefficiencies due to the inability to seamlessly transition between communication mediums, leading to time-consuming and resource-intensive interactions, particularly in voice-based and text-based systems, and lack of customer choice in preferred communication methods.
Innovation Solution
Systems are developed to transition telephony or in-person interactions to and from AI chat sessions using AI chatbot models, enabling seamless communication through SMS, mobile app, email, or web-based interfaces, and utilizing authentication and intent tokens to facilitate efficient and personalized interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If voice-based communication systems (telephony, IVR, call centers) are used for customer service, then real-time interaction and natural language processing are enabled, but the system lacks persistent records, is difficult to follow, and requires significant human staffing resources
Solution Approach 1:
The system performs preliminary actions by capturing customer information during initial voice interactions and storing it in a persistent database. Authentication tokens are pre-generated and stored, allowing subsequent interactions to skip lengthy authentication processes. Customer profiles are created in advance with preferred communication channels documented, enabling seamless transitions without repeated setup.
Solution Approach 2:
The system creates digital copies of customer information, interaction history, and authentication data that can be accessed across different communication channels. Voice interactions are transcribed and stored as text records. Authentication tokens are copied and transferred between telephony and text-based systems, eliminating the need for repeated authentication and enabling seamless channel transitions.
2Loss of information
If text-based communication systems are used for customer service, then persistent records and detailed information display are provided, but the system cannot effectively handle certain types of customer requests and lacks natural language processing capabilities
Solution Approach 1:
The system merges text-based communication with voice-based communication capabilities by integrating multiple communication channels into a unified platform. Text interactions are combined with voice transcription and natural language processing. The system combines the persistent record-keeping of text systems with the natural language processing strengths of voice systems, allowing customers to switch between modes while maintaining continuous service context.
Solution Approach 2:
The unified communication system performs multiple functions across different channels. A single customer service interaction can begin via voice call, transition to text-based AI chat for detailed information retrieval, and return to voice for complex requests. The system universally handles authentication, information display, natural language processing, and record-keeping across all communication modes through a single integrated platform.
3Adaptability or versatility
If multiple separate communication systems (telephony, text-based, IVR) are deployed to serve different customer needs, then customer choice and specialized functionality are provided, but the systems cannot seamlessly transition between mediums, requiring customers to re-authenticate and re-submit requests
Solution Approach 1:
The system implements a universal authentication and session management layer that works across all communication channels. A single authentication token generated in any channel (voice call, text message, web chat) is recognized and validated by all other channels. The session context is universally accessible, allowing customers to switch between telephony, SMS, mobile app, and web-based interfaces without re-authentication or losing their place in the conversation.
Solution Approach 2:
The system introduces intermediary components including a central session management service, token exchange mechanism, and channel translation layer. These intermediaries facilitate seamless transitions by converting between different communication protocols and formats. When a customer switches from voice to text-based communication, the intermediary services translate the interaction context, maintain session continuity, and enable the AI chatbot to pick up exactly where the voice interaction left off.
4Ease of operation
If human representatives are staffed in call centers and brick-and-mortar locations, then personalized customer service and complex problem resolution are achieved, but the cost is prohibitive and wait times are extended
Solution Approach 1:
The system implements self-service capabilities through AI chatbots that can independently handle authentication, information retrieval, and routine account management tasks. Customers can perform common operations such as checking account balances, reviewing transaction history, and updating personal information without human intervention. The system provides personalized service through AI-driven natural language processing that adapts to individual customer preferences and histories, eliminating the need for human representatives for routine inquiries.
Solution Approach 2:
The system replaces mechanical human-based service delivery with automated AI-driven processes. Voice-based AI chatbots and text-based communication systems substitute for human call center agents and in-person service representatives. The automation maintains personalized service quality through machine learning models that analyze customer behavior patterns and preferences, while dramatically reducing operational costs and eliminating wait times associated with human staffing.
Data Source
AI summary
A system for transitioning a telephony or in-person servicing to an artificial intelligence (AI) chat session. The system may receive a phone call from a user device associated with a user, and transmit a voice request for personally identifiable information associated with the user. The system may also receive and authenticate the requested personally identifiable information and, in response, generate an authentication token. The system may further receive a servicing intent from the user device, and generate a corresponding servicing intent token. Also, the system may generate an API call to an AI chatbot model, transmit the authentication token and the servicing intent token to the AI chatbot model, and map the servicing intent token to a stored servicing intent. Finally, the system may transmit a message to the user device via the AI chat session.