Potential Sciences raises seed round backed by UK Sovereign AI
London startup Potential Sciences, building AI infrastructure for drug discovery, has secured a seed round in the tens of millions of dollars from the UK Sovereign AI fund and Stripe's Patrick Collison.
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giftdetect· the right gift in minutesPotential Sciences, a London-based startup building AI infrastructure for scientific drug discovery, has raised a seed round in the tens of millions of dollars, with backing from the UK government's Sovereign AI fund and Stripe CEO Patrick Collison.
The company combines AI, machine learning and quantum chemistry simulations to help researchers understand how molecules behave and interact. Its approach centres on an AI model trained on the fundamental laws of physics rather than on earlier experimental data. The startup says this could make the AI calculations needed to design chemicals 100 times cheaper than today.
Compute and investors
Beyond capital, the Sovereign AI fund is committing compute capacity to the company, which was founded in November last year. Other participants in the round include Twin Path Ventures, Odyssey, Portfolio Ventures, Blue Wire Capital, rule30, Nauta Capital and Lightfield Equity, alongside angel investment from Collison and other angels. Potential Sciences declined to disclose the exact amount raised or its valuation.
Founder Hatem Helal is a former executive at chip designer Graphcore, which was acquired by SoftBank.
Part of a wider government strategy
The investment is the latest from the Sovereign AI fund, whose mission is to ensure the UK develops, owns and scales key AI companies. Its other bets include chip startup Olix and AI startups Ineffable Intelligence and Callosum.
Joséphine Kant, Sovereign AI Investment Partner, said she first met Helal in Cambridge and that he combines technical excellence with low ego and unapologetic ambition. She added that Potential Sciences has the ambition to become a true frontier lab for chemistry, with the potential to fundamentally change how the field works.
If the physics-first approach delivers the cost savings the company claims, it could widen access to computational chemistry tools that today depend on large datasets and heavy computing budgets. For now, those figures are the startup's own claims.
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