Startup accelerates engineering simulations with AI
Fainite AG has received CHF 150,000 from Venture Kick to develop a physics-based AI engine that significantly accelerates engineering simulations. The aim is to automate complex, computationally intensive analyses, thereby reducing development costs and bringing products to market faster.
Hardware development and material testing today rely heavily on physics-based simulations for design, validation and production. These calculations often take hours or days and incur high costs, which delays projects and pushes back production launches. Engineers therefore often reduce model complexity to shorten calculation times, at the expense of accuracy and proximity to real operating conditions.
Physics-aware AI for faster workflows
Fainite is developing a physics-aware AI platform that speeds up and simplifies existing simulation workflows. The engine learns from physics-based simulations and can derive accurate predictions without relying on large historical data sets. Engineers set up new workflows in minutes, run simulations much faster and can intelligently reuse previous results, even with limited amounts of data. An integrated AI agent guides them through complex steps, suggests settings and makes advanced analyses usable for broader teams.
cHF 150,000 for scaling and market entry
The CHF 150,000 from the Venture Kick programme will be used to expand the technology to additional engineering disciplines and use cases and to build a scalable platform with next-generation functionalities. At the same time, the funds will strengthen the team structure and go-to-market activities in order to accelerate deployment at industrial companies. The company is thus addressing around 9 million hardware engineers worldwide whose work is currently slowed down by slow, complex simulation processes.
Founding team with physics and AI expertise
The start-up was founded by researchers and engineers from Caltech, ETH Zurich, the University of Cambridge and Google, including CEO Alex Donzelli, Chief Scientist Prof Burigede Liu and ML Lead Matthias Bonvin. The team is complemented by former executives from established simulation software manufacturers, bringing together in-depth expertise in deep learning, computational physics and industrial simulation platforms. According to Alex Donzelli, Venture Kick’s funding, feedback and network have been instrumental in moving quickly from technical validation to the first industrial applications.