Autonomous Procurement System Using AI for Bidder Selection
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Solution Overview
Problem
Conventional procurement systems are limited by requiring human intervention and lack a holistic, autonomous solution, leading to inefficiencies and increased costs, as well as challenges in capturing all issues and training complexities.
Innovation Solution
An autonomous procurement system that uses AI, blockchain, natural language processing, and machine learning to automate the entire procurement process from pro forma contract creation to selecting a winning bidder, eliminating the need for human intervention and enhancing the integrity of the procurement process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional procurement systems use human intervention for each step, then the process can handle complex scenarios and make intuitive decisions, but the system requires significant human resources, increases payroll costs, and reduces processing speed
Solution Approach 1:
The procurement system performs self-service by automatically executing the entire procurement workflow without human intervention. The system autonomously creates pro forma contracts, scrapes the web to identify bidders, registers suppliers, authenticates information, selects bidders, issues solicitations, evaluates proposals, and creates final contracts. This self-service capability eliminates the need for human operators at each step while maintaining full functional capability.
Solution Approach 2:
The patent replaces the mechanical human decision-making system with an automated AI-based system. Machine learning models and natural language processing algorithms substitute for human intuition and judgment in evaluating bids and making procurement decisions. This substitution maintains decision quality while dramatically increasing processing speed and eliminating payroll costs associated with human procurement staff.
2Adaptability or versatility
If conventional procurement systems require human intervention at each step, then the system can handle complex procurement scenarios, but the device complexity and operational overhead increase significantly
Solution Approach 1:
The autonomous procurement system is designed as a universal platform that handles multiple procurement scenarios through a single integrated system. The same core infrastructure supports various procurement types (goods, services, construction), different bidding methods (open bidding, selective bidding, negotiated bidding), and diverse evaluation criteria. This multi-functionality reduces system complexity compared to having separate manual processes for each procurement scenario.
Solution Approach 2:
The system manages complexity by parameterizing procurement configurations. Instead of hardcoding different procurement scenarios, the system uses configurable parameters and variables that can be adjusted to match different procurement needs. The pro forma contract uses a variables matrix that can be dynamically modified based on the specific procurement scenario, allowing the same system structure to adapt to diverse requirements without increasing operational complexity.
3Productivity
If the system automates the entire procurement process without human intervention, then productivity and processing speed increase, but the system must handle information authentication and bidder selection accuracy challenges
Solution Approach 1:
The system implements feedback loops for information authentication. When supplier information is scraped from the web or submitted during registration, the system automatically verifies and authenticates the data against multiple sources. The machine learning models continuously learn from authentication outcomes, improving their ability to verify supplier credentials, commercial license information, and bank account details. This feedback mechanism ensures high reliability in automated information verification.
Solution Approach 2:
The system performs preliminary authentication and verification actions before the main procurement process. Supplier information is authenticated in advance during the registration phase, and potential bidders are pre-screened based on their credentials and capabilities. This preliminary action ensures that only verified, qualified suppliers enter the bidding process, maintaining high reliability while enabling automated processing throughout the subsequent procurement stages.
4Extent of automation
If the system uses web scraping to identify potential bidders, then the system can autonomously find qualified suppliers without human input, but the system must process and evaluate large volumes of unstructured data
Solution Approach 1:
The system replaces manual data processing with automated natural language processing and machine learning algorithms. These AI-based systems efficiently parse unstructured web data, extract relevant supplier information, and structure it for evaluation. The computational complexity is handled by sophisticated algorithms that can process large volumes of unstructured data far more efficiently than manual human review, maintaining low operational complexity despite high automation extent.
Data Source
AI summary
Systems and methods include a computer-implemented method for autonomous bidder solicitation and selection. A pro forma contract defined by a variables matrix of variables is created from a received procurement request. The web is scraped to identify potential bidders based on the variables. Suppliers are registered, including obtaining, through an on-line registration process, supplier registration information including commercial license information and bank account information for each supplier. Supplier registration information of the suppliers is authenticated. Bidders for the contract are selected, including creating a bidder list identifying suppliers who are to be invited to participate in bidding. Solicitations of interest are issued to bidders identified in the bidder list, the solicitations of interest including a statement of work. Bidding parties are evaluated to identify qualified bidders. A winning bidder is selected from the bidding parties. A final contract is created for the winning bidder.