Industrial & construction procurement is a complex and mostly manual process. This often leads to purchase decisions being made in a rushed, inefficient and error prone manner. Errors lead to waste, higher costs, and increased emissions. According to McKinsey, digital procurement & supply chain optimisation are crucial to addressing these issues, and to unlocking productivity gains in the construction industry. The AI sourcing agent project aims to automate industrial procurement processes using AI, such as large language models (LLM). With this project, we are creating a solution to collect data from procurement processes for both customers and suppliers in the manufacturing and construction industries. Based on this highly domain specific data we can then build and train AI agents that can act as purchasing agents. This means that individual agents will assess different suppliers, match demand and supply, and find the best possible solutions or products amongst an ever growing catalogue of products and offerings. By introducing such a procurement automation layer, while maintaining human oversight (developing a ‘human-in-the-loop’ approach) is going to reduce errors, costs, and emissions.
WHAT DO YOU WANT TO DO?
The AI sourcing agent project aims to automate industrial procurement processes using AI, such as large language
models (LLM). As a consortium of one research institute and two SMEs targeting industrial applications, we are
creating a model to collect data from procurement processes for both customers and suppliers in the manufacturing
and construction industries. We are building and training AI agents that will assess different suppliers and match
demand to reduce errors, costs, and emissions.
WHY DO YOU WANT TO DO IT
Digital procurement & supply chain is identified as key to unlocking productivity gains in the construction industry
(McKinsey). Up to 20% of all purchases are done hastily due to prior errors or unexpected changes to (Cronvall
Research), triggering search for the missing items. Most purchasing is done over email and calls, leading to back and
forth communication which is prone to errors. Errors lead to waste and excess emissions. One third of European waste
comes from construction (WGBC). With AI agents, the correct products are easier to find and errors can be avoided,
unlocking productivity for the entire industry.
HOW WILL YOU MAKE MONEY
By applying AI agents to our online marketplaces we will make money by charging suppliers a monthly Software-as-aService (SaaS) Subscription and invoicing buyers through a transactional fee and commission on the value of sold
products. After the project, we forecast €14 million annual revenue which can be scaled up to €140 million over time.
Our competitive advantage is based on the AI agent learning: the more transactions the AI agent facilitates, the better
the agent becomes. The better the AI agent is, the more transactions it can facilitate. As a result, customers can save
even 16% of material costs (WEF).