LuminX Targets Supply Chain Ops with $5.5M

Logistics delays and inventory errors that once passed as routine are now profit killers, and outdated warehouse systems and inaccurate forecasts have only added on to those problems. Across every sector that relies on logistics (retail, e-commerce, pharmaceuticals, construction) supply chain leaders are realizing that old systems are too outdated and brittle for today’s business needs.

This makes it fertile ground for AI-powered tools and advancements like predictive analytics for SKU demand, AI-powered robotics, and vision systems that eliminate human error from inventory audits, that are enhancing logistics. “AI allows an operation to be more cost effective, precise, visible and efficient,” says Andre Luecht, Zebra Technologies’ global strategy lead for transport and logistics to Logistics Management magazine. “Reduced inventory, accelerated operations, increased visibility and optimized use of equipment, systems and people” are now within reach.

One of the newest entrants in the space is LuminX, a 4-month old San Francisco-based startup that just closed a $5.5 million seed round led by 1Sharpe, GTMFund, 9Yards, Chingona Ventures, and the Bond Fund. LuminX is one of a growing number of AI-focused supply ops platforms aiming to automate what has traditionally been tedious, manual, and error-prone work.

What sets LuminX apart in what is soon to be a crowded market? According to its founders, it’s the combination of Vision Language Models (VLMs) and edge-based hardware, which allows warehouses to gain real-time visibility without the complexity and cost of centralized servers. “This pivotal funding allows us to scale our next-generation AI models, transforming how warehouses operate,” said CEO Alex Kaveh Senemar who co-founded the company with CTO Mohammedreza Javanmardi. “Our edge-based vision language models represent a massive step forward, acting as an intelligent core for warehouse operations.”

Instead of requiring massive infrastructure changes, LuminX’s solution can be mounted on docks, forklifts, conveyors, or deployed as handheld devices. These systems can automatically recognize products, read labels, assess damage, and track movement. The company says it turns “previously opaque processes into transparent, highly efficient systems.”

LuminX’s tech is already making an impact. Robert Bascom, COO of Vertical Cold Storage, noted, “LuminX’s technology is set to revolutionize our warehouse productivity and operations. It’s allowing us to automate critical tasks, significantly enhance quality, and reduce claims.”

The startup’s recent rise is because of an emerging, broader trend. Companies like Blue Yonder, GreyOrange, and Swisslog are racing to implement AI at scale. DHL Supply Chain has built a 200-person data analytics department dedicated to AI and is using it to improve stocking levels and cycle counts at 3PL sites. “Ultimately, we’d like to present real-time data to operators and shift work as equipment is available,” says Eric Walters, VP at DHL to Logistics Management magazine.

Supply and logistics as an industry is making a calculated bet on AI. According to McKinsey, 70% of supply chain leaders expect to shift to real-time, data-driven operations by 2025, up from just 25% in 2022. And the 2025 Stanford AI Index identifies supply chain optimization, especially in pricing and inventory management, as the leading domain for AI ROI, with 70% of companies reporting revenue increases from AI use in corporate strategy and finance.

Despite this progress, implementation is no easy feat. Clean data remains a barrier. Legacy systems often lack the integration needed for accurate AI outputs, with AI projects likely to fail due to poor data foundations.

Still, LuminX is betting that the next decade of logistics will be defined by the ability to automate, optimize, and act in real time. For building materials and retail, the edge-based VLM approach promises reduced errors, better labor utilization, and shorter lead times.

LuminX and companies like Rippey AI, Konexial, and Greenscreens.ai are tackling different pain points with their solutions, which can allow them to coexist. Rippey AI automates back-office functions using conversational AI and machine learning, streamlining tasks like shipment creation, customer service, and even payment processing through its partnership with PayCargo. Konexial brings AI to the road, integrating video safety systems and live telemetry data to proactively monitor driver behavior and optimize fleet safety. Meanwhile, Greenscreens.ai is transforming freight brokerage with dynamic, predictive pricing tools that blend real-time market data with historical transactions to help logistics providers maximize margins.

As AI adoption accelerates, early movers are gaining ground. According to the Stanford AI Index, 78% of organizations now use AI in at least one business area, but only those focusing on supply chain, service ops, and finance are seeing the most financial gains. For suppliers and distributors, that means: those who treat AI as a core operational strategy will have the biggest gains in cost reduction, customer satisfaction, and resilience.