Kevin Coy

It’s an exciting, transformative period for the global supply chain. After several years of disruptions from the pandemic, high-stakes labor challenges, and unstable global trade, supply chain innovators are looking to future-focused solutions that can help logistics professionals not just survive, but thrive in this complex environment. In this article, we explore nine FreightTech solutions (in no particular order) that are making a significant impact in 2024. 1. Axle: Streamlining Back-Office Operations with AI Axle Technologies is modernizing the logistics industry by leveraging artificial intelligence to streamline time-consuming back-office operations. Their universal data platform simplifies access to logistics data, enabling companies to optimize deliveries, reduce fuel costs, and enhance the sustainability and profitability of trucking. Axle embraces diversity, collaboration, and the 80-20 rule, understanding that customer feedback is essential for innovation. By wrangling diverse data sources into a universal schema, Axle is building the transportation infrastructure of tomorrow, making the industry more efficient and resilient. 2. EAIGLE: Enhancing Visibility with AI EAIGLE uses AI to provide unprecedented visibility into operations at gates and yards. Their end-to-end AI platform works with existing or third-party hardware, including optical and infrared cameras and radar sensors. This hardware-agnostic approach ensures superior accuracy, eliminating false…

Special Guest Blog Post written by Matt McKinney, Co-Founder and CEO of Loop   I spend most of my time with supply chain and innovation leaders at major enterprises who are sitting on significant AI budgets but struggling to show measurable business impact in an increasingly complex and volatile supply chain environment.   These conversations have evolved dramatically. A year ago, executives were asking basic questions about AI feasibility. Today, the questions have shifted to strategic implementation at enterprise scale.   Based on hundreds of these discussions, three questions consistently emerge that separate companies making transformational progress from those stuck in pilot purgatory.   How do we move from AI experiments to enterprise-scale impact?   Most organizations have yet to see organization-wide, bottom-line impact from AI use. This is the strategic challenge keeping C-suite leaders awake at night.   The problem isn’t the technology. It’s the application of the technology. Too many enterprises are trying to treat AI like a magic wand they can bolt onto existing systems. But garbage in, garbage out. If your underlying data is fragmented and inconsistent, AI won’t solve your problems; in fact they’ll get worse.   At its core, anything automated is powered by…