Automotive supply chains are under constant pressure from multi-tier volatility, resulting in an estimated $30B of waste each year. Planners spend more than half their time reacting to unforeseen disruptions rather than managing proactively, which leads to inefficiencies, missed opportunities, and heightened costs across the value chain. This reactive mode of operation has made it increasingly difficult for businesses to forecast accurately and maintain resilience in an ever-changing market.
To address these challenges, Calfus partnered with a leading Automotive Technology company to co-create an agentic AI platform that reimagines supply chain planning and execution. Built on a modern, cloud-native architecture, the solution integrates AI/ML engines for predictive insights, workflow orchestration layers for end-to-end process automation, and secure API connections that unify ERP and supplier systems into a single, reliable data fabric. At its core is Jenae, an AI assistant that improves demand forecasting accuracy by anticipating disruptions and empowers teams with real-time recommendations, while streamlining workflows, automating routine tasks, and enabling seamless collaboration across supplier networks.
With this platform, the company gained the ability to forecast demand more accurately, anticipate disruptions before they escalate, and respond with agility to market shifts. By empowering teams with timely insights and reducing planner time spent on reactive problem-solving, the solution improved operational efficiency, strengthened supplier collaboration, and delivered measurable cost savings. The result is a more resilient, adaptive, and intelligent supply chain that drives both immediate efficiencies and long-term competitive advantage.
