A San Francisco startup offering inventory automation and visibility tools has raised $5.5 million in funding for its technology that analyzes photos and videos with artificial intelligence (AI) to solve inefficiencies in supply chain and warehouse management.
LuminX says it uses Vision Language Models (VLMs), a type of AI that enabling machine vision cameras to “see” and interpret dynamic warehouse environments in real-time—recognizing products, varied labels, assessing package conditions, and tracking movement.
According to chip-making giant Nvidia, vision language models are multimodal AI systems built by combining a large language model (LLM) with a vision encoder. That ability allows VLMs to process and provide advanced understanding of video, image, and text inputs supplied in the prompt to generate text responses.
LuminX says it plans to deploy its VLM technology directly onto low-cost mobile hardware within the warehouse, including docks, conveyors, on forklifts, or as handheld units. LuminX’s AI can then process visual information inside the DC to automate intricate operational tasks, eliminate manual work, and provide actionable data for reducing discrepancies and optimizing overall workflow.
The seed round was supported by a multitude of investors, including 1Sharpe, GTMFund, 9Yards, Chingona Ventures, and the Bond Fund.
According to investor Kat Collins of 1Sharpe Capital, “Edge-deployed vision-language models are breaking the two toughest bottlenecks in logistics—labor scarcity and data blindness. By turning a low-cost camera into a perceptive co-worker that sees, understands, and acts in real time, LuminX is unlocking a step-change in operational intelligence and efficiency for every pallet, conveyer, and forklift.”
