UK start-up CuspAI is set to raise $400m in a funding round that includes Amazon founder Jeff Bezos, quadrupling its valuation to about $2.6bn, the Financial Times reported. The two-year-old Cambridge company applies generative AI to materials science research, a field attracting significant investment from tech giants and venture capital firms.
Rapid valuation growth
In September last year, CuspAI was valued at just $520m. The new round would push that figure to $2.6bn, according to FT sources. Investors include Silicon Valley venture capital firm Kleiner Perkins and Bezos Expeditions, the Amazon founder's family office. Term sheets have been signed but the deal is not yet closed.
Founders and high-profile supporters
CuspAI was founded by Max Welling, a professor of machine learning at the University of Amsterdam and a pioneer of AI's application to science, and serial founder Dr Chad Edwards. Its advisory board includes Turing Prize laureate Yann LeCun and Nobel laureate Professor Geoffrey Hinton. Nvidia CEO Jensen Huang named the company as one of the UK start-ups to watch last year, and Nvidia's venture arm participated in its Series A round, which raised over $200m. Angel backers include OpenAI co-founder Durk Kingma, Google VP of Research Zoubin Ghahramani, Dropbox co-founder Arash Ferdowsi, and Hugging Face founder Thomas Wolf.
Applying AI to materials discovery
The company describes itself as "a frontier AI company that specialises in using generative AI and molecular simulation to accelerate the discovery of breakthrough materials for industrial applications across semiconductors, energy, and climate." Its work sits at the intersection of AI for Science & Research and industrial R&D. Bezos himself is pursuing similar goals through his physical AI venture Prometheus, which raised $10bn in April, highlighting the competitive race to apply AI to materials and physical sciences.
Why this matters for Science & Research
The $400m injection signals strong investor confidence that AI can meaningfully speed up materials discovery-a traditionally slow, experiment-heavy process. For research scientists, familiarity with generative AI and molecular simulation tools is becoming a valuable career asset. An AI Learning Path for Research Scientists can help professionals build the skills needed to contribute to this emerging field.
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