Two teenage founders walked into Y Combinator co-founder Paul Graham’s backyard with an idea no one in agriculture seemed to want — an AI model to help design better pesticides. By the time they left, they had a new business model, a new company, and eventually, Graham’s backing.
Now, that reimagined company — Bindwell — has raised $6 million in a seed round, co-led by General Catalyst and A Capital, with a personal check from Graham himself. Rather than selling AI tools to legacy agrochemical giants, the startup is using its own models to design new pesticide molecules in-house and license the IP directly — a shift in strategy aimed at modernizing a legacy industry still dominated by decades-old chemistry.
Pesticide use in agriculture has doubled over the last three decades, yet up to 40% of global crop production is still lost to pests and diseases every year, per the UN Food and Agriculture Organization. As pests evolve and develop resistance, farmers are forced to use increasing amounts of chemicals just to maintain the same yields — a cycle that damages ecosystems and accelerates resistance even further. Regulatory pressure is mounting, but most agrochemical companies still rely on tweaking legacy compounds. Bindwell is betting that AI can break the cycle by discovering entirely new, more targeted molecules — ones designed from scratch for modern challenges.
Founded in 2024 by Tyler Rose, 18, and Navvye Anand, 19, Bindwell adapts AI-led drug discovery techniques to agriculture, with the goal of speeding up how new pesticide molecules are identified and tested.
Bindwell began as a research project in late 2023, when Rose and Anand were students at the Wolfram Summer Research Program. They initially focused on a drug discovery AI model called PLAPT, which involved binding affinity prediction — work that was later cited in a Nature Scientific Reports paper on cancer therapeutics. In 2024, they began exploring how the same approach could be applied to pesticides.
Both founders had personal exposure to the problem. Rose learned about the challenges of pest control from his aunt, who farms in China. Anand, who has roots in Punjab, saw firsthand how limited pesticide options affected crop yields.
“Agriculture has been in our mind space,” said Rose in an interview. “That led to the realization that we can use the exact same technology that has been successful in drug discovery. We can bring that over to pesticide discovery, because the biochemistry is the same, but pesticides are such a big problem, and I feel like it’s not very focused on by most people.”
Rose and Anand entered Y Combinator’s Winter 2025 batch with plans to build AI models and sell their access to major agrochemical companies. But they did not find traction — most industry players were reluctant to adopt AI as a core part of pesticide discovery. Midway through the program, they were invited to Paul Graham’s home, where they spoke with him for about 45 minutes on the back patio.
After hearing about their challenges, Graham suggested a different approach: Rather than selling tools, they could use their own models to discover new pesticide molecules themselves. That conversation marked the beginning of Bindwell’s current direction.
“The founders [of Bindwell] will probably do alright,” he later posted on X. “They’re smart and have a good idea.”
Bindwell has developed its own AI suite designed to reduce hallucination — a common issue where models produce unreliable or unsupported outputs. The software includes Foldwell, a structure prediction model, which is a custom diffusion system inspired by DeepMind’s AlphaFold, used to identify target protein structures. It also includes PLAPT, an open source protein-ligand interaction model capable of scanning every known synthesized compound in under six hours, and APPT, a protein-protein interaction model for biopesticide screening, reported to outperform existing tools by 1.7× on the Affinity Benchmark v5.5. Moreover, the suite incorporates an uncertainty quantification system that flags when results are trustworthy and when more data is needed.
“Since we’re not selling AI models, we’re not competing with companies that sell models,” Rose told TechCrunch.
Together, Bindwell’s models can analyze “billions” of molecules, the startup said, and deliver four times faster performance than DeepMind’s AlphaFold 3.
“The way most pesticides are discovered right now is not target-based,” said Rose. “Entomologists and chemists suggest different compounds, then test them on insects. You often need to synthesize and test thousands of chemicals, which is expensive just to check for efficacy. With our AI models, you’re able to simplify the problem down to a single protein.”
The AI helps identify proteins that are unique to a specific pest but absent in humans, beneficial insects, or aquatic organisms like water fleas.
“Once you find those proteins, you can design something that binds to them and stops them from working,” Rose said.
Bindwell is currently testing the efficacy of its AI-generated molecules at its lab in San Carlos. It is also working with a third-party partner to further validate the models, though Rose declined to share details.
Rose said the startup is in early discussions with several global agrochemical firms, with its first partnership deal expected to close soon. “A year from now, we want to be entering into our licensing deals with some of these companies,” he said. Bindwell has also begun talks with stakeholders in India and China to conduct field tests.
The startup currently has a team of four, and also works with external contractors for molecule synthesis.
Bindwell’s seed round also included participation from SV Angel, alongside Graham. Prior to joining Y Combinator’s Winter 2025 batch, the startup raised a pre-seed round from Character Capital.