AI-Guided GUI for Resource Transfer Prioritization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies fail to efficiently manage complex transactions involving multiple disparate systems and decentralized data resources, relying on subjective factors and lacking centralized workflow management, which hinders effective interconnection of transfer sources, destinations, and intermediaries.
Innovation Solution
A computing system utilizing artificial intelligence and natural language processing to create an integrated platform with a customizable workflow, where user data is used to identify resources and assign probability scores, prioritizing listings for transfer destinations, and facilitating resource transfer through a series of GUIs for data entry and workflow management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple disparate systems are used to facilitate complex transactions, then various data resources and communication systems can be accessed, but the systems cannot be effectively interconnected and lack centralized workflow management
Solution Approach 1:
The patent combines multiple disparate systems into a single integrated platform that provides centralized workflow management. The system merges transfer sources, transfer destinations, intermediaries, and third-party data sources into one cohesive environment with unified access controls and workflow orchestration, eliminating the fragmentation of separate systems while maintaining the ability to access diverse data resources.
Solution Approach 2:
The integrated platform is designed as a universal system that can handle multiple types of transactions and access various data resources through a single interface. The workflow management system provides multi-functional capabilities including resource identification, probability scoring, listing generation, and transfer facilitation, allowing one system to perform the functions previously requiring multiple separate systems.
2Adaptability or versatility
If subjective factors are used for transaction assessments, then agent experience and intuition can be leveraged, but the assessments are not standardized and lack consistency
Solution Approach 1:
The system implements feedback mechanisms where AI models analyze user data and activities to generate probability scores that reflect both objective metrics and patterns learned from agent expertise. The workflow management system continuously refines assessments by comparing outcomes with expected results, standardizing the evaluation process while incorporating the nuanced judgment that comes from experienced agents through trained AI models.
Solution Approach 2:
The patent transforms subjective assessment parameters into standardized quantitative metrics through AI processing. User data, activities, and resource characteristics are converted into probability scores and structured parameters that maintain the informational value of expert judgment while enabling consistent, repeatable measurements across different transactions and agents.
3Productivity
If AI models are used to identify resources and assign probability scores, then resource allocation can be optimized, but the system requires collecting and processing extensive user data
Solution Approach 1:
The system extracts only the essential data elements needed for AI processing from user activities and interactions. Rather than collecting and processing all possible user data, the workflow management system identifies and extracts specific parameters such as user preferences, activity patterns, and resource characteristics that are most relevant for probability scoring and resource identification, reducing the data burden while maintaining allocation efficiency.
Solution Approach 2:
The AI model is designed to process data in a self-service manner, automatically collecting and analyzing user information through existing platform interactions without requiring explicit data submission. The system leverages naturally occurring user activities, such as browsing behavior and transaction history, to gather necessary data for probability scoring, minimizing additional data collection requirements while maintaining productive resource allocation.
Data Source
AI summary
Systems and methods initiate displaying a first GUI of an integrated platform that interconnects transfer source(s) and transfer destination(s), wherein access to the integrated platform is restricted to registered users, and end user data of at least one of the transfer destination(s) are at least partially obtained from user responses to system prompts displayed via the first GUI and from user activities of user(s) of the transfer destination(s). End user data is applied to a deployed AI model to identify resource(s) available for transfer to generate a listing of the resource(s), and a probability score indicating a likelihood the user(s) will be interested is assigned to the resource(s) and sorted to prioritize highest scored resources. Display of a customized second GUI including the listing of the resource(s) is initiated.