Intent-Based Messaging Routing Between Bots and Terminal Devices
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Solution Overview
Problem
Existing systems struggle to dynamically and efficiently route communications between network devices and terminal devices, particularly in complex environments with multiple clients and agents, failing to account for variations in communication topics, channel types, and agent availability.
Innovation Solution
A connection management system that facilitates strategic routing by evaluating communication content, agent profiles, and network dynamics to establish and manage connection channels, monitor exchanges, and apply real-time adjustments for optimal routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated bot routing is implemented, then response speed and system efficiency are improved, but adaptability to complex communication scenarios and nuanced intent recognition deteriorate
Solution Approach 1:
The patent introduces an intelligent routing system as an intermediary between the bot automation system and terminal devices. This routing system analyzes communication content, determines user intent, and selectively routes interactions to appropriate terminal devices when bot automation is insufficient. The routing system acts as a mediator that bridges automated processing and human-operated terminal devices, enabling the system to maintain high productivity through bot routing while preserving adaptability by escalating complex scenarios to terminal devices.
2Productivity
If dynamic routing based on real-time metrics is implemented, then communication efficiency is improved, but system complexity and computational requirements worsen
Solution Approach 1:
The patent implements preliminary action by pre-establishing routing rules, intent classification models, and performance thresholds before operational use. The intelligent routing system is pre-configured with criteria for determining when to route to bots versus terminal devices, and pre-trained with intent recognition capabilities. This preliminary preparation reduces real-time computational complexity during actual communication routing, as the system只需 apply pre-defined rules and pre-trained models rather than performing complex analysis from scratch for each interaction.
3Measurement precision
If feedback loops for model training are implemented, then future intent recognition accuracy is improved, but data processing time and computational resources worsen
Solution Approach 1:
The patent implements continuous feedback loops where performance data from bot interactions and terminal device escalations are continuously collected and used to retrain the intent recognition model. This continuous learning process operates in the background without interrupting normal communication routing operations. The system maintains a steady stream of data collection, model training, and performance optimization, ensuring that intent recognition accuracy improves over time while minimizing disruption to productive operations through asynchronous processing.
Data Source
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AI summary
The present disclosure relates generally to facilitating routing of communications. More specifically, techniques are provided to dynamically transfer messaging between a network device and a terminal device to a type of bot based on intents identified from the messaging. Further, techniques are provided to track performance of the selected type of bot during automation.