Artificial Intelligence
Applied models for scientific work — perception, prediction and lab automation. AI is the instrument that reads every other instrument here.
Each domain runs its own experiments — and shares data, tooling and people with the other four. Move through the modules; the instrument reassembles itself.
Applied models for scientific work — perception, prediction and lab automation. AI is the instrument that reads every other instrument here.
Engineering biology as a tool — from assay design to organism-scale measurement, with data pipelines built for wet-lab reality.
Field trials, crop sensing and decision models that help growers act on evidence rather than averages.
Early-stage discovery support — target analysis, formulation data and screening workflows that shorten the path to a candidate.
The physical layer of the lab: sensors, edge devices and custom instruments we design when the right tool doesn’t exist yet.