In an increasingly unpredictable and interconnected world, companies are often forced to react quickly to sudden changes: geopolitical crises, production disruptions, rising costs, or new regulations can threaten entire supply chains. In this scenario, finding alternative suppliers in a timely manner is not just a competitive advantage but a strategic necessity. This is where Industry 5.0 technologies and artificial intelligence (AI) come into play in business processes.
Extraction of data from corporate texts
As outlined in previous articles, one of the most useful tools in these scenarios is KYD®: a solution that enables the extraction of data from corporate texts (RFQs, technical specifications, procedures), the generation of insights from technical documents, and more generally, the optimized management of unstructured data. The NLP technologies powering KYD® can be repurposed for multiple objectives. In this article, we explore how our knowledge management technology can be adapted to support the procurement function.
AI Tools for Procurement: From Manual Search to Semantic Intelligence
Traditionally, automated supplier searches relied on structured catalogs and rigid filters. Today, thanks to NLP applications tailored to evolving business needs, it is possible to analyze requirements expressed in natural language and quickly find compatible solutions. The match between supply and demand no longer depends on simple code or keyword matching, but can now occur through deep semantic analysis that understands the technical, commercial, and strategic context of the company.
More specifically, the supplier selection process can now be guided by AI, using intelligent algorithms that understand business needs and compare them with supplier profiles and offerings—going well beyond standard product or sector classifications. But do tools built for this specific purpose really exist?
The Matchmaker Tool: Simplifying Complexity
A concrete example of this approach is the Matchmaker Tool, developed by Erre Quadro as part of the Horizon RaRe2 project. It is a web application that integrates a semantic search engine with an intuitive user interface, enabling fast and targeted exploration of potential suppliers. At the heart of the system is an NLP-based algorithm (AI supply chain matching) that connects supplier offerings with users’ specific needs.
The main screen of the Matchmaker displays a comprehensive list of supplier offerings, ordered alphabetically to ensure neutrality and ease of consultation. It features an advanced search bar and a filtering/sorting system, allowing users to customize their exploration according to their specific criteria.
Depending on how the tool is configured, users can begin by filtering suppliers by country, company size, or industry. Alternatively, they can use semantic search: by entering a detailed request in the search bar, an intelligent algorithm interprets the content and returns targeted results. For example, a query such as “AI-based predictive analytics tools for the supply chain” will yield specialized suppliers in that sector. According to the client’s needs, each result can include a detailed profile with descriptions, location, company size, and other optional metadata.
These details enable effective comparison and evaluation of supplier alternatives. The platform also facilitates direct communication with suppliers or the sending of RFQs, making the path from research to engagement smooth and structured.
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A Use Case from the RaRe2 Project
In times of disruption, acting quickly is critical. For example, if a company detects signs of instability in a key supplier—such as delays or financial troubles—the user can activate the Matchmaker to quickly find equivalent alternatives. This reduces the risk of production stoppage, fostering a responsive and adaptive supply chain. The following example illustrates one such use case developed within the RaRe2 project.
A manufacturing company specializing in the production of boxes is struggling with a sudden increase in raw material costs. This price spike directly threatens profit margins and makes current pricing unsustainable for clients. Moreover, the search for alternative suppliers is often slow and inefficient, increasing the risk of production delays.
To address this challenge, the procurement manager decides to use the Matchmaker. By entering specific parameters of interest, the tool instantly returns a list of compatible suppliers, including useful information for evaluation.
This fast, need-driven process strengthens operational resilience and ensures production continuity, even when issues arise with primary suppliers. Additionally, the strategic visibility gained over the entire supplier ecosystem allows the procurement team to act more proactively, building a diversified and reliable supplier network. Ultimately, the Matchmaker proves to be a key tool for turning risk into an opportunity for optimization and sustainable growth.
Conclusions: Artificial Intelligence in Service of Responsiveness
Procurement is no longer just an operational function but a strategic domain where innovation plays a crucial role. The benefits of supplier matchmaking platforms go beyond faster scouting they improve decision quality and risk anticipation capabilities. In a world of increasing complexity, where supply chains are global and interdependent, tools like Matchmaker are game-changers. By integrating AI procurement tools into business workflows, companies not only respond better to emergencies but also build more resilient, intelligent, and sustainable supply chains.
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