Although for several years, companies have been investing massively in artificial intelligence to optimize their logistics operations, the physical chain remains largely under-instrumented. The majority of product movements and states remain invisible, due to a lack of continuous and reliable data at the level of each item.
The emergence of a new generation of battery-free sensors and tags aims to resolve this problem. These devices seek to combine the reduced cost of RFID with close-in performance of active sensors, paving the way for a physical data layer capable of powering large-scale predictive and operational models.
One of the major challenges concerns granularity because existing systems mainly capture one-off data, attached to scans or crossing points. The promise of continuous, item-level instrumentation has so far only been achieved in limited cases, often at the cost of expensive devices.
In this context, several North American players are banking on hybrid architectures combining microelectronics, advanced radio frequencies and software infrastructures ready for AI. The first applications affect environments where visibility is most lacking, such as dynamic inventory management, incoming and outgoing flows, anomaly detection or preventive maintenance. As data becomes continuous, AI models can be recalibrated in real time rather than from static images of activity.
The challenge is no longer just optimization, but resilience, and the ability of companies to anticipate rather than react.
This dynamic is part of INLAN, a Montreal deeptech startup, which has developed a battery-free IDO tag and a software infrastructure intended to support large-scale data collection. According to Ali Shajii, CEO of INLAN, the aim is to address a structural gap: “AI is poised to fundamentally transform supply chain management, but only if the underlying data is granular, real-time, multi-dimensional and reliable. This level of data simply does not exist today at scale.” Mohammad Hajikhani, co-founder and product manager, explains the technological choice: “Over the past two years, we have developed a new class of battery-free tag, which combines the affordability advantages of RFID with the performance of active IoT devices.”
In a market still dominated by fragmented and often expensive solutions, the ability to produce and deploy such labels on a large scale remains decisive. Manufacturers expect devices that are simple, robust, energy efficient and compatible with existing systems. This equation, long considered out of reach, is now attracting the attention of investors specializing in industrial technologies and applied AI models.
INLAN announces Series A financing of 5 million US dollars, or 4.25 million euros. The round is led by Saas Fee Limited, with the participation of Shea Ventures, deeptech studio TandemLaunch and business angels. Founded by Ali Shajii and Mohammad Hajikhani and based in Montreal, the company develops battery-free IoT tags and software infrastructure designed to enable continuous data collection at the individual item level. This funding must support the industrialization of the equipment, the deployment in real logistics environments and the extension of the data platform.
