Nvidia alumni established Vsim, which raises $21.5 million for robotics simulation technology

Nvidia has made significant strides in developing processors that support complex, high-performance graphical simulations, useful for everything from gaming to AI training and industrial applications. Now, two engineers who played a key role in creating these simulations have secured substantial seed funding for their new venture.

The startup, Vsim, based in Manchester, is building an innovative physics simulation platform and has raised $21.5 million from EQT Ventures and several other investors. This recent funding brings Vsim’s total raised to $24 million and values the company at approximately $100 million. Participants in the funding round included Factorial Fund, Samsung Next, Tru Arrow, Xora (a Temasek subsidiary), IQ Capital, Koro Capital, Concept Ventures, Lakestar Scout Fund, and Carles Reina.

Despite operating under the radar so far, Vsim is focusing on developing technology for robotics training. Co-founder Michelle Lu, who launched the company alongside Kier Storey, revealed to TechCrunch that their initial efforts are aimed at the robotics sector, but the technology has broader potential applications. The duo’s background includes over a decade of experience at Nvidia, working on advanced simulation technology, following their time building physics engines at Bizarre Creations, a Manchester-based game studio acquired by Activision.

Lu and Storey began their entrepreneurial journey right after completing their PhDs but faced challenges due to the limited funding environment for simulation technology startups in Northern England in 2007. Their current venture, however, is set to capitalize on significant advances in processing power and algorithm efficiency, which make specialized applications of simulation technology more viable.

Sandra Malmberg, a partner at EQT Ventures, explained that Vsim’s platform is designed to handle the complexity of real-time decision-making in dynamic environments, a capability lacking in existing simulation tools. This new technology could initially benefit robotics, with potential future applications across various sectors, including research, entertainment, manufacturing, and pharmaceuticals.