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Our Mission: We aim to accelerate and automate chemical process development by equipping wet-lab chemists with the power of data-driven optimization and robotic execution of experiments. The Problem: The discovery of novel pharmaceuticals is one of our most important weapons in fighting disease. However, the drug development pipeline is often held up for many months during the design of chemical processes to manufacture these drugs at scale, delaying FDA trials and lengthening the time until drug launch. Designing chemical processes involves the identification of suitable parameters such as catalyst/temperature/solvent. Currently process development is often done via tedious trial-and-error experimentation (slow) or exhaustive screening (expensive and wasteful). Our Approach: In our research, we have developed algorithms for chemical process optimization, which leverage transfer learning and Bayesian optimization. We validated the algorithms in the wet lab, showing an up to 95% reduction in required experiments and cost compared to exhaustive screening. We have made our approaches accessible to chemists through our user-friendly no-code software platform and to automated laboratory equipment with our API.

Seals is a suite of AI Employees for Wholesalers & Distributors. Instead of relying on humans to quote, take orders, collect payments, place purchase orders and enter data into ERPs. We build AI Employees that do these manual repetitive tasks for the 700k wholesalers in the US. We’re a team of three Computer Science majors, and Fernando launched and grew AT&T in Mexico to $120M ARR. Previously, we all worked together at our last YC-backed startup, building it to over $6M in revenue. It was there that we placed thousands of purchase orders with wholesalers. We realized that almost every physical product comes from B2B sales in the supply chain. However, it turns out that most of these operations are still done manually through phone and email, involving tasks like quoting, taking orders, collecting payments, entering data into ERPs, and providing support. By automating these tasks with AI agents in a human-like manner, we are creating a massive opportunity to convert $100B of payroll expenses into software spending.