AI Suitability Model for Overseas Bid Filtering

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Solution Overview

Problem

South Korean companies face a low market share in international public procurement due to difficulties in obtaining and filtering relevant bid notices from overseas buyers, lack of competency in international bidding processes, and a shortage of professional labor and experience.

Innovation Solution

An artificial intelligence and machine learning-based system that uses a suitability analysis model to match company information with bid notices from overseas procurement buyers, extracting and transmitting optimal bid notices suitable for each company by evaluating matching suitability based on common information and requirements.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If companies manually search and filter bid notices from overseas procurement markets, then they can obtain bidding information, but the process is time-consuming and inefficient due to the large volume of bid notices posted daily

Engineering Contradiction:

Improvebid notice filtering efficiencyVSAvoidtime to obtain and filter bid notices

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical searching and filtering of bid notices with an AI-based automated system. The suitability analysis model uses machine learning algorithms to automatically process, analyze, and filter bid notices from overseas procurement markets, eliminating the need for manual review of large volumes of documents and significantly reducing time consumption while improving filtering efficiency

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the AI model to autonomously perform bid notice filtering and suitability analysis without human intervention. The model automatically learns from procurement data, adapts to different buyer requirements, and independently generates customized bid notice lists for companies, freeing employees from repetitive manual filtering tasks

Inventive Principle:

Principle #25Self-service

2Reliability

If companies manually analyze and match bid notices with company profiles, then they can identify relevant opportunities, but the process requires significant professional labor and expertise that is in short supply

Engineering Contradiction:

Improvebid notice suitability accuracyVSAvoidprofessional labor requirements

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces complex manual analysis requiring professional expertise with an automated AI-based suitability analysis model. The model processes bid notice metadata and company profile information using machine learning algorithms, automatically determining matching suitability and generating customized bid notice lists. This eliminates the need for highly skilled manual analysis while maintaining or improving accuracy through sophisticated pattern recognition and data processing capabilities

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The AI suitability analysis model acts as an intermediary between bid notices and companies, automatically performing the matching function that previously required human professionals. The model translates complex bid notice requirements and company capabilities into automated comparisons, producing reliable match results without requiring intermediaries to be human experts in international procurement

Inventive Principle:

Principle #24Intermediary (Mediator)

3Adaptability or versatility

If companies focus on domestic public procurement markets, then they can easily access bid information, but they miss out on opportunities in the larger international public procurement market

Engineering Contradiction:

Improvemarket participation scopeVSAvoidoverseas bid notice availability

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The patent implements universality by creating a multi-functional system that simultaneously handles both domestic and international procurement markets through a single unified platform. The suitability analysis model is designed to process bid notices from various sources including international organizations and multilateral development banks, while also accommodating domestic market requirements. This allows companies to access and filter bid notices from diverse international markets without needing separate specialized systems for each market type

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system replaces manual international bid notice collection and filtering with an automated AI-based information gathering and processing mechanism. The model automatically scrapes, collects, and analyzes bid notice metadata from multiple international sources, processes company profile information, and generates customized matching lists. This automated approach overcomes language barriers and access difficulties that previously limited companies to domestic markets

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20240257230A1Artificial intelligence and machine learning-based overseas public procurement customized bidding information provision service system and method

Publication Date: 2024.08.01 KIM MAN KI

AI summary

Disclosed are an artificial intelligence and machine learning-based overseas public procurement customized bidding information provision service system and method. The disclosure can provide optimal bidding information suitable for a corresponding company by matching company information, in which domestic companies meet international bidding requirements, and bidding information, which is collected from procurement information of overseas procurement owners, by using an AI-based suitability analysis model.