A Startup Just Raised $3.7 Million to Help Make Fusion Power Real
A startup called Fusionality, based in Lausanne, Switzerland, has raised $3.7 million (CHF 3 million) in early funding to build control systems and simulation tools for companies developing fusion reactors. The round was backed by two venture capital firms, Founderful and Playfair. TechCrunch
The company was founded in 2026 by Federico Felici and Jonas Buchli. Felici serves as CEO and Buchli as CTO. TechCrunch
Fusionality is initially focusing on magnetic confinement fusion. This is the approach where powerful magnetic fields hold superheated gas, called plasma, inside a reactor so that fusion reactions can take place. The company plans to build control systems and simulation environments that fusion startups can adapt to their own reactor designs. TechCrunch
Felici and Buchli met while teaching AI to control a type of fusion reactor called a tokamak at EPFL, a university in Switzerland. Felici worked at EPFL, while Buchli worked at Google DeepMind. Felici later moved to Google DeepMind, where he developed simulations and machine learning tools for fusion devices. TechCrunch
Felici said fusion companies told him there is no one providing control-system components that 'speak the language of fusion.' TechCrunch
According to the company's website, fusion organizations face a common bottleneck: too few experts are available worldwide to build the systems needed to measure, understand, and control plasma inside a reactor. Fusion devices need to measure plasma behavior, interpret it instantly, and adjust the plasma in real time. Fusionality
The website also states that Fusionality's technology provides real-time diagnostics for fusion device operations. It describes the company as providing measurement, control, and data systems for the fusion era, with a mission to help fusion teams analyze, operate, and control their devices with confidence. Fusionality
The broader context here is the coming together of two trends this publication has tracked for years: artificial intelligence is now good enough to help control complex physical systems, and private investment in fusion energy has surged. At Google DeepMind, Buchli and Felici worked at the intersection of both. Their plan to build control systems and simulation tools that can be sold to fusion companies targets a real gap. Fusion reactors need to control plasma in real time, reacting in less than a thousandth of a second. There are simply not enough specialists to build custom control systems for every new reactor design. If Fusionality can deliver adaptable control-system components, it could help reactor startups move faster instead of each one needing to hire its own team of specialists.
Worth flagging: the gap between raising early funding and actually deploying a working control system in a fusion reactor is large. Fusionality is entering a field where control-system failures carry physical risk, not just a software glitch. Testing and validating these systems will take years, not months. The company's ability to build trust with reactor developers and show that its simulations can accurately model plasma behavior will determine whether it becomes an essential part of the fusion industry or remains an ambitious concept. The $3.7 million gives the team time to build, but the path to real adoption runs through working with actual experimental reactors.
In this author's view, what Fusionality is doing mirrors what happened in the self-driving car industry about a decade ago. General-purpose AI tools existed, but the companies that built specialized software for autonomous vehicles created lasting value because they understood the specific physics and timing requirements of driving. Fusionality is making a similar bet: that control software built specifically for fusion, by people who have hands-on experience with reactors and AI, will be more useful to reactor developers than off-the-shelf industrial software.
The optimism here is warranted but measured. Fusion energy has absorbed decades of investment and engineering effort without delivering power to the grid. The current wave of private fusion startups has shortened the timeline rhetoric, but achieving fusion that produces more energy than it consumes remains an unsolved engineering problem. Fusionality is not promising to solve that problem. It is promising to build the control and simulation tools that other companies need to solve it faster. That is a narrower and more credible claim than another startup promising commercial fusion by the end of the decade. If the company delivers on its initial plans, it will give reactor developers one fewer reason to reinvent infrastructure and one more reason to focus their scarce talent on the physics problems that remain.
