Monarch
Join Login

Crop damage begins with an insect’s decision to land.

Learn

A global scientific effort to turn insect behavior data into training data. Our models learn which kinds of compounds are most likely to change an insect’s decision to land on crops.

Proudly partnering with leaders in global health, crop protection, and machine learning.

  • University of Toronto, Chemical Engineering & Applied Chemistry
  • United States Department of Agriculture
  • Rutgers University, Philip E. Marucci Center for Blueberry & Cranberry Research, New Jersey Agricultural Experiment Station
  • NVIDIA Inception Program
  • Ifakara Health Institute
  • Kenya Medical Research Institute (KEMRI)
  • Spatial Repellents, University of Notre Dame
  • Dweck Lab
  • Lambda
  • Google Cloud
  • Spectrum Impact

Insect behavior data to crop protection.

Goal 01 ·

Run 50,000 behavior-rich assays a month and share results within 24 hours of each run.

Goal 02 ·

Predict how at least 75% of new compounds change spotted wing drosophila landing behavior.

Goal 03 ·

Scale-up at least three formulations that reduce spotted wing drosophila crop damage by at least 50% compared with current options.

Insect behavior data → training data → compounds that change an insect’s decision

CONTROL
COMPOUND 127

Ask questions across every assay, compound, and result.

Get an Ask Monarch setup code from your lab portal, then connect it to Claude, Codex, or your terminal.

What we’ve done so far.

2,289 SWD tube trials to date
102 Compounds screened
32 Contact assay recordings
50,000 assays Target · not yet reached