Omnichannel Response Engine for Cross-Channel Data Adaptation
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Solution Overview
Problem
Conventional electronic messaging platforms are limited in their ability to provide automated responses across different data protocols and communication channels, leading to inefficiencies and redundant resource usage, as they are typically designed to function within specific communication channels and have limited functionality.
Innovation Solution
An automated predictive response computing system that identifies and adapts to various data types, including voice and text, across disparate communication channels, using an omnichannel transceiver, feature extraction controller, predictive intent controller, and automated voice-text response engine to generate conversational flows independently of the communication channel or payload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional bot applications are implemented to provide automated responses, then automated response functionality is achieved, but the system is limited to specific communication channels and protocols
Solution Approach 1:
The patent implements a universal bot application architecture that can operate across multiple communication channels (social media, messaging platforms, voice channels) and data protocols simultaneously. The system uses a common data model and response generation engine that adapts to different channels through configuration rather than requiring separate bot instances, thereby achieving multi-functionality without proportionally increasing complexity.
Solution Approach 2:
The patent introduces an intermediary layer (omnichannel transceiver and universal data model) between the communication channels and the bot application logic. This mediator translates various channel-specific protocols into a unified internal representation, allowing the bot to operate independently of the specific communication channel while maintaining adaptability to different platforms.
2Reliability
If separate bot applications are deployed for different communication channels, then channel-specific functionality is optimized, but redundant resources are required
Solution Approach 1:
The patent merges multiple channel-specific bot applications into a single unified bot application that handles multiple communication channels concurrently. By combining the response generation logic, data processing, and state management into one shared system, the patent eliminates redundant resources while maintaining channel-specific optimization through the universal data model and configurable channel adapters.
3Adaptability or versatility
If traditional server architectures are used to support multiple communication channels, then comprehensive coverage is achieved, but the system requires redundant resources and suboptimal performance
Solution Approach 1:
The patent segments the traditional monolithic server architecture into modular components: a universal bot application core, channel-specific adapters, and a shared data model layer. This segmentation allows the system to support multiple channels efficiently by processing each channel's data through specialized adapters while sharing common processing logic and resources, thereby improving productivity without sacrificing multi-channel support.
Data Source
AI summary
Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to implement automated responses to data representing electronic messages, among other things, and, more specifically, to a computing and data platform that implements logic to facilitate implementation of an automated predictive response computing system independent of electronic communication channel or payload of an electronic message payload, the automated predictive response computing system being configured to implement, for example, an automated voice-text response engine configured to build and adaptively implement conversational data flows based on, for example, classification of an electronic message and a predictive response. In some examples, a method may include detecting an electronic message includes inbound voice data, analyzing inbound voice data, invoking an automated response application, and selecting a response, among other things.