Dynamic Portal AI for Request Intake Guidance
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Solution Overview
Problem
Conventional request intake systems are not user-friendly, failing to identify and alert users of missing or inconsistent information and lacking educational guidance during the submission process, while also not interfacing effectively with other systems to submit generated text documents.
Innovation Solution
A dynamic portal system that uses natural language processing and machine learning to analyze user requests, identify issues, determine relevant rules, and provide educational information, while interfacing with electronic filing systems to submit completed documents and generate alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional request intake systems are used, then the system structure is simple, but the user experience is poor due to lack of identification and alerting of missing or inconsistent information
Solution Approach 1:
The patent introduces an AI processor as an intermediary component between the user portal and the request processing system. This AI processor analyzes intake requests, identifies issues, and provides alerts about missing or inconsistent information, thereby improving user experience without requiring complete system restructuring
Solution Approach 2:
The patent replaces manual review processes with automated AI-based analysis. The AI processor uses natural language processing and machine learning models to automatically identify issues in intake requests, substituting human operators and reducing system complexity while improving ease of operation
2Ease of operation
If conventional request intake systems are used, then the system is simple, but educational guidance is not provided during the submission process
Solution Approach 1:
The patent implements a feedback mechanism where the AI processor analyzes intake requests and provides real-time alerts and educational guidance to users about missing or inconsistent information. This feedback loop improves ease of operation by guiding users through the submission process while maintaining manageable system complexity through automated processing
Solution Approach 2:
The system enables users to self-correct their intake requests by providing them with specific alerts about missing or inconsistent information. Users can independently identify and fix issues based on system feedback without requiring external assistance, improving ease of operation while keeping the system relatively simple
3Adaptability or versatility
If conventional request intake systems are used, then the system architecture is simple, but effective interface with other systems for document submission is not achieved
Solution Approach 1:
The patent makes the AI processor a universal component that can interface with multiple different systems (electronic filing systems, case management systems, etc.). This single AI processor handles various document types and submission formats, improving adaptability while managing software interface complexity through a unified approach
4Productivity
If manual review of intake requests is performed, then system complexity is low, but productivity and completeness of requests are reduced
Solution Approach 1:
The patent replaces manual review processes with automated AI-based analysis. The AI processor uses natural language processing and machine learning to rapidly analyze intake requests, identifying issues and determining completeness automatically. This substitution dramatically improves productivity while managing system complexity through standardized processing algorithms
Data Source
AI summary
At least some aspects of the present disclosure direct to systems and methods of dynamic portals implemented on a computer system having one or more processors and memories. The methods includes the steps of: presenting a user portal comprising an interactive region and an informational region; receiving an intake request submitted by a user via the interactive region, the intake request being a text stream; analyzing the intake request to identify an issue associated with the intake request; determining at least one rule of a plurality of rules relevant to the issue; selecting one or more pieces of educational information from a rule repository based on the at least one relevant rule; and updating the user portal.