Hybrid Guided Communication System for Automated Live Support
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Solution Overview
Problem
Current web applications for user inquiry handling are resource-intensive and difficult to navigate, with live support being labor-intensive and chat-bot solutions facing challenges in providing accurate automated responses due to user inquiry description difficulties and reliance on scripted solutions.
Innovation Solution
A hybrid system and platform that combines automated and live support by processing user inquiries through one or more processors, determining if an automated response is available by comparing the inquiry to a database, and providing either automated or live responses based on availability, with the ability to stream the user's application or web browser state for guided support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If live support is provided to users, then user experience is improved, but labor intensity increases
Solution Approach 1:
The support system is segmented into automated response generation and live human review components. The automated system handles routine inquiries and generates draft responses, while human agents only intervene for complex or sensitive cases, thereby reducing overall labor intensity while maintaining quality
Solution Approach 2:
The system enables self-service through automated response generation where AI handles common customer inquiries independently. This allows the system to serve itself for routine tasks, reducing the need for human intervention and lowering labor intensity while maintaining reliable user experience
2Extent of automation
If chat-bot support is used, then automation is increased, but response accuracy decreases
Solution Approach 1:
A human-in-the-loop intermediary mechanism is introduced where human agents review and validate automated responses before they reach users. This intermediary layer corrects errors and ensures accuracy while preserving the benefits of automation for handling volume
Solution Approach 2:
The system implements feedback loops where user responses and agent corrections are continuously fed back to improve the automated response generation model. This iterative feedback process enhances response accuracy over time while maintaining high automation levels
3Adaptability or versatility
If web applications are made more comprehensive, then functionality is improved, but ease of navigation deteriorates
Solution Approach 1:
Complex navigation and information retrieval tasks are extracted from the user interface and handled automatically by the AI system. The AI interprets user intent and directly retrieves relevant information, removing the need for users to navigate through complex application structures while preserving comprehensive functionality
4Productivity
If automated response systems are implemented, then productivity is improved, but adaptability to unique inquiries decreases
Solution Approach 1:
The system dynamically adjusts its operation mode based on inquiry characteristics. For routine inquiries, it operates in fully automated mode for high productivity. For unique or complex inquiries, it dynamically transitions to human agent mode, ensuring adaptability. This dynamic switching optimizes both productivity and adaptability
Data Source
AI summary
Systems, methods, and computer-readable media are provided for hybrid guidance of a communication session. In one aspect, a system includes one or more processors configured to execute computer-readable instructions to receive an inquiry from a user terminal; stream the inquiry to one or more support terminals configured to provide live support for the inquiry; determine if an automated response to the inquiry is available; and provide one of the automated response or a live response to the inquiry based on whether the automated response to the inquiry is available or not.