We're developing better, safer pesticides using our state-of-the-art AI models.
We're teenage engineers on a mission to develop new pesticides for a safer, healthier, and more bountiful world.
Today, we’re launching Foldwell, our breakthrough structure prediction model that runs 4x faster than AlphaFold 3. Foldwell is just one piece in a suite of ground-up models we've built for every step of the pesticide discovery pipeline.
❌ The Problem:
Pesticides are failing us: Their usage has doubled since 2000, even though farmland has decreased. Yet, we still lose 20-40% of crops to pests.
Resistance makes things worse: Pests evolve resistance, forcing farmers to use even more pesticides to get the same results. This creates a vicious cycle of increasing resistance and collateral damage.
Innovation is stagnant: Since the 2010s, fewer than 40 new active ingredients have been introduced. Most “new” pesticides are just minor tweaks of existing chemicals.
Industry left behind: AI has revolutionized drug discovery; pesticide discovery is overdue for the same transformation because the underlying biochemistry is similar.
Making better pesticides is hard: The ideal pesticide kills only the target pest and nothing else—current solutions are bad at this.
We use AI to build better pesticides.
Because pesticide discovery is a search problem, speed is key: In mere seconds, our AI models give us biological assays that would have traditionally taken days—completely changing the game for pesticide discovery.
We've built these AI models so far:
Foldwell: our AlphaFold replacement that’s 4x faster, used to identify target structures.
PLAPT: Insanely fast open-source protein-ligand interaction model that can scan every synthesized compound known to man in just 6 hours.
APPT: State-of-the-art protein-protein interaction model for biopesticide screening, outperforms existing models by 1.7x on Affinity Benchmark V5.5.
We’re currently mapping druggable proteins in select harmful species that are notoriously difficult in the industry in order to find candidates with high specificity.
We’re Navvye Anand (Caltech) and Tyler Rose (Wolfram Research), a scrappy duo of engineers who met at the Wolfram Summer Research Program in June 2023. We’re Indo-Chinese founders who both grew up visiting farmlands in our countries. United by our passion for tackling hard problems, we dropped out of college and started Bindwell to transform the archaic agrochemical industry.
We’re joined by Max, a prodigious hacker and open source contributor who dropped out of a math degree at Reed College. Max is relentlessly curious about everything from robotics to philosophy, and like us, his passion for solving challenging problems made him a perfect fit for the team.