Conversation-Based Computing System for Mobile User Interaction
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Solution Overview
Problem
Enterprise software systems face challenges in efficiently interacting with users on mobile devices, as form-based applications can be cumbersome and time-consuming, and voice call-based interfaces are expensive and inefficient, particularly in collecting user information and resolving user issues.
Innovation Solution
A conversation-based system that facilitates interaction between users and enterprises through a design module defining conversation models, an execution module for executing these models, and protocol adapters for various communication protocols, allowing for partially or fully automated conversations that adapt to user needs without requiring complex navigation or human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If form-based applications are used for user interaction, then user information can be collected systematically, but the interface becomes cumbersome and time-consuming to use on mobile devices
Solution Approach 1:
The patent replaces the mechanical form-filling interface with a voice-based natural language conversation interface. Users speak naturally instead of manually navigating forms, which eliminates the cumbersome interaction while maintaining systematic information collection through structured conversation flows that guide users to provide necessary details.
Solution Approach 2:
The system changes the interaction mode parameter from visual form-based input to audio-based conversational input. This parameter change allows the system to collect the same structured information through a fundamentally different interaction paradigm that is more suitable for mobile devices, where voice input is more convenient than typing or form navigation.
2Ease of operation
If voice call-based interfaces are used for user interaction, then user issues can be resolved through natural conversation, but the system becomes time-consuming and expensive to implement
Solution Approach 1:
The system implements dynamic conversation flows that adapt in real-time based on user responses and system state. The conversation structure is flexible and can be optimized during execution, allowing the system to resolve issues efficiently by following the most direct path to resolution rather than adhering to rigid scripted call flows.
Solution Approach 2:
The system enables self-service through automated conversation bots that can independently resolve common user issues without requiring human agent intervention. The automated system collects information, processes requests, and provides solutions through natural language conversations, eliminating the need for time-consuming transfers to live agents for routine matters.
3Productivity
If traditional enterprise systems are used, then operational processes can be managed, but the system requests users to provide irrelevant information and fails to meet user needs
Solution Approach 1:
The system implements continuous feedback loops where user responses are analyzed in real-time to adjust the conversation flow and information requirements. The system learns from user interactions and adapts to individual user needs, dynamically modifying which information is requested and how the conversation proceeds, thereby eliminating requests for irrelevant information while maintaining operational efficiency.
Solution Approach 2:
The system performs preliminary actions by proactively gathering context information and pre-processing user needs before the main interaction occurs. The conversation model is pre-configured with knowledge of required information structures, allowing the system to guide users efficiently through only the necessary questions rather than requesting all possible information upfront.
4Productivity
If fully automated conversation systems are implemented, then operational efficiency is improved, but the system lacks human intervention for complex issues
Solution Approach 1:
The system uses a hybrid architecture where an automated conversation system serves as the primary interface for routine matters, with seamless escalation paths to human agents for complex issues. The automated system handles the majority of interactions efficiently, while human agents are available as intermediaries for situations requiring judgment, empathy, or complex problem-solving that exceeds automated capabilities.
Solution Approach 2:
The system applies partial automation selectively - fully automated for routine, well-defined tasks, and partially automated with human oversight for more complex scenarios. This partial automation approach maintains high efficiency for common operations while preserving human intervention capabilities when needed, rather than attempting full automation across all scenarios.
Data Source
AI summary
A conversation-based computing system may include a back-end computing module, a design module, and an execution module. The design module may be configured to provide a graphical user interface through which different conversation models are defined in metadata. Each model may include a topic containing respective goals, where the goals are associated with respective conversation flows that define respective dialogs that directs conversations toward the associated goals. Each model may also define references to topic-specific content stored in the back-end module. The execution module may be configured to execute a particular model between the system and a front-end computing device and set up integration of a live agent into the model. Execution of the model may involve, in part, carrying out, in an at least partially-automated fashion, the flow for the model according to the dialog, the topic-specific content corresponding to the model, and communicating using a specific communication protocol.