A Strategic Investment for Advanced Chip Manufacturing

Invisix, a company focused on semiconductor metrology, has announced the closing of an oversubscribed €20 million seed funding round. The investment saw participation from prominent players such as Hitachi Ventures, Transition Ventures, imec.xpand, Doosan Investment Co., and a tier-one semiconductor manufacturer. This capital is earmarked to support the development of next-generation measurement tools, which are essential for the production of increasingly complex and miniaturized chips.

The growing complexity and shrinking dimensions of semiconductor devices make it increasingly challenging to measure critical structures within advanced chips. Manufacturers must verify each layer before proceeding to the next, yet conventional optical metrology tools can no longer resolve many of the internal and "buried" features that determine device performance. As these chips power sectors like High-Performance Computing and Artificial Intelligence, the demand for faster, non-destructive measurement solutions capable of improving yields and accelerating production is constantly growing.

HHG Technology: Soft X-rays for Three-Dimensional Insights

Founded by Christina Porter and Sietse van der Post, both with backgrounds at ASML and PhDs in physics, Invisix is developing a soft x-ray metrology platform. This technology is designed to enable high-volume, non-destructive measurement of even the most challenging semiconductor structures. Co-founder and CEO Christina Porter emphasized how the increasing complexity and three-dimensional nature of advanced semiconductors are driving demand for a new generation of metrology tools capable of inspecting critical internal structures without damaging devices.

Invisix's technology is based on High Harmonic Generation (HHG), a process rooted in scientific discoveries recognized by the 2023 Nobel Prize in Physics. HHG uses a short-pulsed laser to excite noble-gas atoms into a high-energy state, causing them to emit soft x-rays across multiple wavelengths. This generates a richer three-dimensional signal than conventional single-wavelength laser systems. By combining HHG with proprietary reconstruction algorithms and machine learning, Invisix reconstructs detailed three-dimensional images of internal device structures without damaging the wafer. The system architecture has also been designed to deliver the throughput required for high-volume semiconductor manufacturing.

Impact on Chip Production for AI and HPC

Invisix applies to metrology the same principle that transformed semiconductor lithography: as device dimensions shrink, the wavelength used to measure them must shrink as well. By using soft x-rays, the company aims to provide visibility into buried nanoscale structures that are increasingly inaccessible to conventional optical inspection methods. This capability is crucial for the production of next-generation chips, which are the beating heart of AI and HPC infrastructures, both in the cloud and on-premise.

The technology has already been validated through industry collaborations, including work with Intel and imec. The company continues customer demonstrations from its new cleanroom facility in Eindhoven. For those evaluating on-premise deployments, the availability of cutting-edge hardware with guaranteed performance and reliability from the production phase is a decisive factor in the Total Cost of Ownership (TCO) and infrastructure planning. AI-RADAR offers analytical frameworks on /llm-onpremise to evaluate these trade-offs.

Future Prospects and Commercial Acceleration

With the new funding, Invisix will focus on expanding its team, accelerating the development of its first commercial system, and supporting customer demonstrations at the new cleanroom facility in Eindhoven. The goal is to bring the first commercial system to market and enable semiconductor manufacturers to measure the next generation of advanced devices at production scale.

This development is particularly relevant for the AI-RADAR sector, as innovation in chip metrology directly translates into improved quality and availability of silicon for Large Language Models inference and training. The ability to produce denser, higher-performing chips with high yields is a fundamental prerequisite for the evolution of the computing capabilities required for the most demanding AI workloads, whether in self-hosted or air-gapped environments.