A machine failure on a factory floor can turn a highly automated production line into an expensive stoppage. Swedish industrial AI company IPercept is tackling that problem by giving manufacturers a way to see how CNC machines are changing while they operate, using precise motion data rather than relying on conventional controller information. The company has now raised $16.5 million in Series A funding to take its technology into the US and expand its platform.
The round was co led by Isogon Ventures and London based 2150, with existing investors Luminar Ventures, RunwayFBU, J12 Venture and AI.Fund also participating.
The new capital will support US expansion, including the company’s first local hires, as well as continued development of its hardware and software platform.
Turning Machine Motion Into Data
IPercept describes its technology as a fitness tracker for industrial machines. Instead of waiting for a machine to fail or relying solely on scheduled maintenance, its system continuously analyses how a CNC machine moves to identify changes that can indicate mechanical degradation.
The company’s Smart IIoT Device is mounted on the machine’s kinematic chain, on the moving side where component wear can be detected. It captures high precision motion data and sends the information to IPercept’s software, where diagnostic models analyse the machine’s condition.
The approach does not require access to the machine controller or a major IT integration project. IPercept says its technology can work across CNC machines regardless of manufacturer, model, age or control system.
From Wear to Action
The objective is not simply to collect another stream of factory data. IPercept’s platform is designed to identify which components are changing, how their condition is developing and what action maintenance teams should consider.
Its Machine Health service provides component level information on areas including bearings, ball screws, guides and spindles. The platform can also provide remaining useful life information, identify abnormalities and prioritise maintenance actions.
This shifts maintenance away from fixed schedules toward condition based decisions. Instead of replacing a component simply because it has reached a predetermined service interval, manufacturers can use information about its actual condition to decide when intervention is required.
One Device, Multiple Applications
IPercept’s platform goes beyond predictive maintenance. The company offers services covering machine health, process load monitoring, utilisation tracking and spindle dynamic testing.
Process Load Monitoring can track mechanical loads on spindle and feed drives, while Utilisation Tracking provides information on whether machines are powered off, idle or actively working. Spindle Dynamic Test is designed to identify rotational speed ranges where spindle behaviour may become unstable.
Together, these capabilities give manufacturers a broader picture of machine performance rather than focusing only on breakdown prevention.
Expanding Across Manufacturing
IPercept has already moved from research into industrial deployments. The company says its technology is used across more than 50 machine brands and has reported customer deployments across sectors including aerospace, automotive, energy, equipment manufacturing and mining.
In February 2026, IPercept also announced a collaboration with the University of Sheffield Advanced Manufacturing Research Centre to deploy its technology on selected CNC machines and study predictive maintenance and process monitoring in high value manufacturing.
The company has also been expanding through industrial service partnerships. A 2026 agreement with Machine Tool Technologies in the UK is intended to bring IPercept’s predictive maintenance platform to more manufacturers through an established CNC service network.
Taking Industrial AI to the US
IPercept was spun out of Sweden’s KTH Royal Institute of Technology and began commercialisation in 2022. Its latest funding gives the company resources to establish a presence in the United States while continuing to develop its technology.
As factories become increasingly dependent on expensive CNC equipment, IPercept is betting that manufacturers will want more visibility into machine health before failures occur. Its approach combines specialised hardware, high precision motion measurement and AI based diagnostics to turn physical changes inside machines into actionable maintenance information.
The company’s broader ambition is to make complex industrial equipment more understandable to software, allowing maintenance teams to replace unexpected breakdowns with earlier, data driven decisions.