Montreal-based company Axya has raised 17 million Canadian dollars (approximately 12 million USD) in a Series A funding round, according to a press release published on September 24. These funds will help enhance the company's platform and artificial intelligence capabilities, as well as enter new markets and hire more staff. Axya was founded by Félix Bélisle-Dockrill, who previously worked in supplier quality for two of the largest manufacturers in the aerospace industry. He encountered difficulties in assessing and managing suppliers, which led him to create the Axya platform for more efficient knowledge and information exchange in the supply chain.
“Despite significant investments in digital transformation, procurement remains one of the most fragmented functions in manufacturing organizations,” – stated Bélisle-Dockrill. “The Axya platform integrates data, suppliers, and workflows that impact procurement decisions, allowing manufacturers to reduce manual labor, increase supplier responsiveness, and create more sustainable supply chains.” Axya helps complex manufacturers make their supply chains more predictable, cost-effective, and sustainable by connecting ERP integrations with AI-based workflows that complement existing procurement teams.
The company specializes in three sectors: aerospace and defense, specialty machinery and vehicles manufacturing, as well as natural resources and processing. Axya collaborates with companies like Infor, Epicor, Oracle, SAP, Microsoft Dynamics, and Sage to connect supplier networks and ERP data. The Axya platform employs a human-in-the-loop approach, allowing procurement teams to remain in control while AI automates the most labor-intensive tasks, such as data normalization, early risk detection, and finding savings opportunities, enabling teams to focus on the most strategic decisions and actions. According to analytics firm IDC, by 2029, 45% of the world's top 2000 companies will use agent-managed supply chains, leading to a 20% increase in revenue and a 30% improvement in partner and customer satisfaction. However, AI agents cannot scale without clean, managed, and compatible data. “Data readiness – is not a preparatory stage, it is a prerequisite for everything that follows.”
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