IPercept has raised $16.5 million in Series A funding to expand its CNC machine intelligence platform into the United States and develop additional software applications around the condition and performance data collected from production equipment.
The Stockholm company, which emerged from research at KTH Royal Institute of Technology, has built a monitoring system that measures the physical movement of CNC machine tools rather than depending on a direct connection to the machine controller. A compact sensor records motion before analytical software converts those measurements into information about component condition and process stability.
The Series A provides capital for the company’s first dedicated US hires, commercial expansion, and a broader software layer around its installed hardware. IPercept says its technology is already live across facilities operated by more than 30 manufacturers, including Airbus, Bosch, Hitachi Energy, Scania, and Volvo.
The approach addresses a familiar problem in factory maintenance. Many manufacturers operate mixed fleets of machine tools accumulated over decades, often with different control systems, proprietary interfaces, software generations, and levels of network connectivity. Extracting comparable data from every asset can become an integration project before engineers receive any useful maintenance information.
IPercept is designed to avoid that dependency. Its hardware does not require modification of the existing machine infrastructure and can be installed independently of the controller, allowing the same monitoring principle to be applied across different machine brands and ages. The company says a standard device requires a 24V power supply and can be installed on a large CNC machine in around 45 minutes.
The system uses high-resolution motion analysis to identify changes in mechanical behaviour around components such as axes and spindles. Those changes can then support condition-based maintenance, allowing engineering teams to investigate deterioration before it develops into an unplanned failure or begins to affect part quality.
Predictive maintenance is not new, but CNC equipment presents a difficult measurement environment because cutting forces, spindle speed, axis movement, tooling, workpiece geometry, and production cycles change constantly. A useful monitoring platform has to separate normal process variation from evidence that the machine itself is degrading.
IPercept says its technology was developed through five years of research before commercialisation began in 2022. Earlier company material described deployments across more than a dozen large European manufacturers; the latest funding announcement puts the installed base across more than 30 manufacturers, indicating that adoption has widened materially.
Research partnerships are providing another validation route. In February, IPercept signed an agreement with the University of Sheffield Advanced Manufacturing Research Centre to deploy its Smart Devices and online services on selected CNC machines. The work is examining machine behaviour, process stability, and the condition of critical components in a high-value manufacturing environment.
The UK is also part of the company’s commercial expansion. An agreement with Machine Tool Technologies gives MTT the ability to integrate IPercept monitoring into its nationwide CNC service operation, combining sensor data with engineers who already maintain machines across aerospace, automotive, defence, medical, and component manufacturing sites.
That service model addresses a limitation common to industrial monitoring software. Detecting a developing condition is useful only if someone can judge whether the diagnosis is credible, identify the physical cause, obtain parts, and complete the repair. Pairing data with experienced service engineers can therefore matter as much as improving the algorithm.
The new funding will also support software applications intended to make the machine data easier to use in production and maintenance decisions. IPercept has already introduced a CNC Copilot product intended to translate machine information into clearer answers about what changed, why it matters, and what action operators should consider.
That is a more demanding proposition than building another dashboard. Manufacturing sites already generate large quantities of machine and production data, and engineering teams have limited value for an additional system that simply visualises trends without helping to narrow the cause of a problem.
The controller-independent architecture also reduces one cybersecurity concern because the monitoring device does not have to be deeply integrated into the machine’s control network. It does not remove the need to secure connected factory systems, but it can simplify deployment where manufacturers are reluctant to connect legacy production equipment to new software platforms.
IPercept raised €5 million in 2025 to scale its predictive AI platform across European manufacturing. The latest $16.5 million Series A moves the company into a larger expansion phase, with the United States becoming a dedicated market rather than an extension of its European sales operation.
US deployment will expose the platform to a much larger and more varied installed machine base. Reliable early identification of mechanical deterioration can move repair work into planned downtime and protect production, while false alarms or vague recommendations create additional work for maintenance teams. The next expansion phase will show whether IPercept can retain that diagnostic consistency as installations multiply.
