ASML Spinoff Invisix Raises €20 Million for Next-Gen Chip Metrology
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ASML Spinoff Invisix Raises €20 Million for Next-Gen Chip Metrology

The Dutch startup uses soft x-ray technology to solve a critical manufacturing bottleneck for chipmakers.

6/1/2026
Ghita Khalfaoui
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Eindhoven-based semiconductor metrology startup Invisix has raised €20 million in an oversubscribed seed round to advance soft x-ray measurement technology for next-generation chip manufacturing. The round includes backing from Hitachi Ventures, Transition Ventures, imec.xpand, Doosan Investment and an unnamed tier-one semiconductor manufacturer, underscoring investor interest in tools that can support the industry’s move toward more complex AI-era devices.


Funding and Market Context

The announcement comes as chipmakers face a growing measurement challenge: advanced logic and memory devices are becoming smaller, denser and more three-dimensional, while conventional optical metrology tools are reaching their practical limits. Manufacturers must verify each layer of a wafer before building the next, but some of the structures that now determine performance and yield are buried too deeply or are too fine for existing optical inspection methods to resolve. When those measurements cannot be performed quickly and non-destructively, chip producers may be forced into slower and more expensive techniques that can delay production ramps.

Technology and Differentiation

Invisix is developing a soft x-ray metrology platform designed to inspect critical internal chip structures without damaging the wafer and with enough throughput for high-volume manufacturing. The system uses high harmonic generation, a process linked to discoveries recognized by the 2023 Nobel Prize in Physics, in which a short-pulsed laser excites noble-gas atoms and produces short-wavelength light across multiple colors. By combining this broadband soft x-ray signal with reconstruction algorithms and machine learning, the company aims to generate detailed three-dimensional information about structures that are difficult for single-wavelength optical systems to capture.

From ASML Research to Commercial Deployment

The startup was founded by ASML alumni and PhD physicists Christina Porter, its chief executive, and Sietse van der Post, its chief technology officer, and it is building on more than a decade of soft x-ray research developed inside ASML. The company has licensed a significant technology package from that work and has recruited veterans of the ASML soft x-ray program, alongside senior industry hires including chief operating officer Roald Dogge, previously COO of Dutch semiconductor contract manufacturer NTS. Invisix has also pointed to earlier demonstrations with Intel and imec, including work on gate-all-around transistor architectures, as evidence that its approach can address some of the industry’s most demanding metrology targets.

Strategic Importance

The company’s pitch reflects a broader shift in semiconductor manufacturing, where yield, process control and time-to-node are becoming as strategically important as raw transistor scaling. AI training, inference and high-performance computing depend on chips that are increasingly complex to manufacture, and the ability to see inside nanoscale structures can influence how quickly new designs move from development to volume production. For Europe’s semiconductor ecosystem, Invisix also represents another example of deep-tech company formation around ASML, imec and the Dutch-Belgian hardware supply chain.


With the new seed funding, Invisix is moving from technology validation toward commercial execution, a difficult transition for any semiconductor equipment startup. Its immediate task is to turn a soft x-ray testbench and proven research base into a reliable tool that customers can evaluate, integrate and eventually deploy in advanced fabs. If the company can meet the speed, accuracy and reliability expectations of high-volume chipmakers, its technology could help close a critical visibility gap in the manufacturing of next-generation AI and computing chips.