Onepot

Combining AI and robotics to automate chemical synthesis
Website
The problem

Every drug, material, or agrochemical starts with the same challenge: you need a molecule that doesn’t exist yet. And still today, making that molecule is painfully slow. Chemists spend weeks synthesising compounds before discovery work can even begin. In a world where AI is transforming biology, chemistry remains one of the biggest bottlenecks.

Location

USA

The solution

Onepot has built a different kind of lab. They combine artificial intelligence and robotics to automate one of the most time-consuming steps in drug development: chemical synthesis. Chemists begin by submitting a target molecule – or selecting one from Onepot’s digital library of 3.4 billion possible compounds, most never synthesised before. From there, their AI model, Phil, takes over. Phil can write protocols, operate lab tools, analyse LC/MS results, detect byproducts, and design new experiments on the fly. In just one month, Phil runs more reactions than a typical graduate student would during an entire PhD.

Investment year

2025

Combining AI and robotics to automate chemical synthesis
Website
Sector

Materials

Investment stage

seed

Combining AI and robotics to automate chemical synthesis
Website
Sector
Materials
Location
USA
Investment stage
seed
Investment year
2025
The problem

Every drug, material, or agrochemical starts with the same challenge: you need a molecule that doesn’t exist yet. And still today, making that molecule is painfully slow. Chemists spend weeks synthesising compounds before discovery work can even begin. In a world where AI is transforming biology, chemistry remains one of the biggest bottlenecks.

The solution

Onepot has built a different kind of lab. They combine artificial intelligence and robotics to automate one of the most time-consuming steps in drug development: chemical synthesis. Chemists begin by submitting a target molecule – or selecting one from Onepot’s digital library of 3.4 billion possible compounds, most never synthesised before. From there, their AI model, Phil, takes over. Phil can write protocols, operate lab tools, analyse LC/MS results, detect byproducts, and design new experiments on the fly. In just one month, Phil runs more reactions than a typical graduate student would during an entire PhD.

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