Google DeepMind’s protein-folding breakthroughs have flooded biopharma with new drug candidates, but testing each one remains slow and costly. That’s where 10x Science comes in. Launched in December 2025 by chemical biologist David Roberts, biologist Andrew Reiter and AI specialist Vishnu Tejus, the startup just closed a $4.8 million seed round led by Initialized Capital (with YC, Civilization Ventures and Founder Factor joining). Their platform merges chemistry-driven algorithms and AI “agents” trained on mass-spectrometry data to turn raw spectra into clear molecular structures. Unlike black-box models, 10x Science can trace every step of its analysis—a must for regulatory compliance. Scientists at Rilas Technologies have run dozens of samples through the platform and report it shaves weeks off their workflows. Matthew Crawford, one of their users, says the AI not only interprets spectra accurately but even infers which protein he’s testing by name and then pulls the sequence from public databases. Previous tools often over-promised or tripped over complex molecules, but 10x Science nails reasonable assumptions, thanks to the founders’ hands-on lab experience in Carolyn Bertozzi’s Stanford group. With seed proceeds in hand, 10x Science plans to hire more engineers, refine its models and onboard pharma clients and academic labs. In the short term, it’s a subscription-based SaaS that pharmaceutical companies must pay to process candidates through the “funnel.” Longer term, Roberts aims to layer cell-level data on top of protein structure to build what he calls “molecular intelligence.” Investors like Initialized’s Zoe Perret see a defensible niche: few teams understand both deep biochemistry and the messy data mass spectrometry produces. If the startup scales, it could become a go-to analytics engine for anyone converting AI-generated candidates into real-world drugs.