AI Resource Routing System for Intelligent Transfer Recommendations
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Solution Overview
Problem
Current systems lack the capability to provide intelligent recommendations and automatically route resources associated with resource entities, necessitating a system that can intelligently route resource transfers.
Innovation Solution
A system comprising processing devices and memory devices with computer-readable program code that continuously monitors channels for resource transfer requests, generates recommendations using an artificial intelligence engine, and routes requests based on entity preferences, third-party preferences, location, speed, and security considerations, either manually through a graphical user interface or automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional systems are used for resource transfers, then system simplicity is maintained, but the capability to provide intelligent recommendations and automatic routing is lost
Solution Approach 1:
The patent introduces an AI engine as an intermediary component between the resource transfer request and the routing decision. This mediator analyzes entity preferences, third-party preferences, location data, and other parameters to generate intelligent routing recommendations, thereby adding adaptability without requiring complete system redesign
Solution Approach 2:
The system segments the routing decision-making process into distinct modules: preference collection, AI analysis, recommendation generation, and execution. This segmentation allows the intelligent routing capability to be added as a separate functional layer, managing complexity through modular design
2Productivity
If manual selection of resource transfer methods is used, then system complexity is reduced, but productivity and efficiency are decreased
Solution Approach 1:
The system implements self-service automation where the AI engine automatically analyzes transfer requests, compares entity preferences with available routing options, and selects the optimal resource transfer method without requiring manual intervention. This increases productivity while maintaining manageable automation levels through configurable parameters
Solution Approach 2:
The system incorporates feedback mechanisms where entity preferences and transfer outcomes are continuously collected and fed back to the AI engine. This feedback loop enables the system to learn from past transfers and improve routing decisions over time, enhancing productivity through adaptive automation
3Manufacturing precision
If comprehensive entity preferences and parameters are collected, then routing optimization is improved, but information processing complexity increases
Solution Approach 1:
The patent extracts and separates the data collection and processing functions into dedicated modules. Entity preferences, third-party preferences, location data, and security parameters are collected and processed independently before being fed to the AI engine, reducing overall system complexity while maintaining routing optimization precision
Solution Approach 2:
The system dynamically adjusts the weight and importance of different parameters based on the specific transfer context. The AI engine can prioritize certain parameters (e.g., security vs. speed vs. cost) depending on the transfer type and entity preferences, optimizing routing precision without requiring equal processing of all parameters
Data Source
AI summary
A system is typically configured to continuously monitor one or more channels, wherein the one or more channels are associated with sources of initiation of resource transfer requests, receive a resource transfer request from a resource entity system via at least one channel of the one or more channels, in response to receiving the resource transfer request, generate, via an artificial intelligence engine, one or more recommendations associated with routing of the resource transfer request, wherein each of the one or more recommendations comprises a resource transfer method, and route the resource transfer request via a resource transfer method associated with at least one recommendation of the one or more recommendations.