Service Coordination System Using ML for Provider Matching

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Solution Overview

Problem

Finding a suitable service provider, such as a financial advisor, is often time-consuming and challenging due to the lack of readily available and accurate information, leading to difficulties in vetting their credentials and expertise, and existing methods do not efficiently match users with the right providers.

Innovation Solution

A computer-implemented method and system that uses a trained machine learning model to pair users with service providers based on user and provider criteria, including personal identification information, credentials, and user feedback, facilitating meetings and scheduling through a service coordination system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If traditional methods (phone book, internet search, referrals) are used to find service providers, then the process is accessible and simple to initiate, but the information availability and accuracy are insufficient for proper vetting of credentials and expertise

Engineering Contradiction:

Improveavailability and accuracy of service provider informationVSAvoidcomplexity of information verification process

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent introduces a third-party verification system that acts as an intermediary between users and service providers. This system collects, validates, and presents verified information about service providers' credentials, licenses, and expertise, eliminating the need for users to manually verify information while ensuring accuracy and completeness of provider data.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs preliminary verification of service provider credentials and expertise before users need to make decisions. By pre-verifying and organizing this information in a structured manner, the system eliminates the need for users to conduct time-consuming manual verification processes while ensuring they receive accurate and reliable information.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If users meet multiple service providers in person to find the right fit, then the quality of matching improves, but the time and effort required increases significantly

Engineering Contradiction:

Improvequality of user-service provider matchVSAvoidtime required for finding and meeting providers

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent replaces the mechanical process of physically meeting multiple service providers in person with an electronic matching system. The system uses algorithms to compare user criteria with service provider profiles and credentials, generating personalized recommendations that eliminate the need for multiple in-person meetings while maintaining high matching quality through comprehensive data analysis.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system transforms the matching process from a manual, qualitative evaluation based on in-person interactions to an automated, quantitative analysis of multiple parameters including credentials, expertise areas, availability, and user preferences. This parameter-based approach enables comprehensive comparison of many providers simultaneously, improving match quality while reducing time requirements.

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If users conduct extensive research and vetting of service provider credentials, then the accuracy of provider selection improves, but the complexity and time required for the process increases

Engineering Contradiction:

Improveaccuracy of service provider evaluationVSAvoidease of vetting process

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs self-service verification of service provider credentials, licenses, and expertise automatically. Instead of requiring users to manually research and verify provider information, the system independently collects, validates, and presents this information in an organized manner, maintaining high evaluation accuracy while making the process extremely easy to operate through automated information gathering and presentation.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20240054548A1Utilizing machine learning models to generate customized output

Publication Date: 2024.02.15 GOLDEN STATE ASSET MANAGEMENT LLC

AI summary

A service coordination system can receive user data and service provider data and can matching and pairing recommendations pertaining to the users and one or more service providers as well as schedule meetings between the users and service providers and facilitate data exchange between a user and a paired service provider. In some embodiments, machine learning and/or artificial intelligence algorithms can be used to match users with service providers (SPs). Additional communications components are also provided for the users and SPs, once matched or paired.