Anthrogen

10x Science develops frontier AI models with deep memory to redefine how scientists understand and engineer biology across the life sciences, starting with drug development. AI-powered drug discovery is flooding the pipeline with new candidates faster than ever. But before any of them can advance to the clinic, scientists must deeply characterize the protein therapeutic to understand whether it will work. Today, that process takes months of manual, error-prone analysis that cannot keep pace with

shared product terms: model, but, protein, therapeutic; shared product theme: health and clinical care; same category: AI infrastructure; shared affiliation: Y Combinator

Trident Bioscience builds tools to expedite the discovery and optimization of useful proteins. Our technology first applies predictive models of protein structure and function to generate sets of potentially active protein sequences. We then apply our state-of-the-art sequence optimization algorithm to design gene libraries capable of testing these candidates extremely quickly and affordably. By combining these technologies, we're closing the design-build-test loop of protein optimization and cu

shared product terms: protein, function, design, model; same category: AI infrastructure; shared affiliation: Y Combinator

Many pressing problems facing humanity can be solved with faster scientific compute. Currently, it takes billions of dollars to design and develop a new fusion reactor, a hyper-sonic airplane or a new cancer treatment. This is because scientists and engineers have to build very expensive things before they even know if their ideas work. But what if we can simulate the workings of these ideas (and more) on computers first and have high confidence that it works before we build really expensive thi

shared product terms: but, design, take, billion; same category: AI infrastructure; shared affiliation: Y Combinator

UrbanKisaan is an AI-for-plant-biology company. We build foundation models and the physical infrastructure that trains them. Shipping a single new seed variety takes about ten+ years. Two on germplasm, three on crosses and selection, three or four on field trials, one on regulatory. Inside that decade, prediction and experiment never properly meet. DNA is abundant, phenotype data is scarce and unpaired, and the cycle never trains itself. We closed that loop. Three foundation models cover the ups

shared product terms: trial, take, decade, train; same category: AI infrastructure; shared affiliation: Y Combinator

Biotechnology is rewriting life as we know it, from the medicines we take, to the crops we grow, the materials we wear, and the household goods that we rely on every day. Biotech R&D is radically transforming our world, but to move at the new speed of science, scientists need better technology. Benchling’s mission is to unlock the power of biotechnology. The world’s biotech leaders and innovators use our R&D Cloud to power the development of breakthrough products and accelerate time to milestone

shared product terms: material, rely, day, but; shared affiliation: Y Combinator

The next decade is going to see a biotech revolution fueled by three technologies: ability to read DNA (sequencing), ability to write DNA (synthesis), and computational systems that predict what DNA to read and write. With sequencing and synthesis being mainstream now [1], 20n provides the computational systems that predict DNA design for novel industrial biotech and health applications. At 20n, we are taking a fresh look at turning biological data into information. We approach it as a big data

shared product terms: decade, ability, now, design; shared product theme: health and clinical care; shared affiliation: Y Combinator