Modern farms produce a flood of sensor data — soil moisture, weather, canopy imaging — and almost none of it becomes a decision. Cropmind changes that. Specialist miner models ingest raw feeds and return concrete guidance: yield forecasts, irrigation timing, and risk alerts a grower can act on today.
The team is mid-incubation with models trained on a first regional dataset and a working pipeline from sensor feed to forecast. Graduation funds the production subnet — competing miners specialize by crop and climate, validators score them against real harvest outcomes.
Team selected into Intake 01
Passed the hybrid community vote · Slot 03 assigned
Regional dataset assembled
First labeled sensor + harvest dataset cleaned and indexed
Forecast pipeline prototype
End-to-end path from raw sensor feed to yield forecast
Multi-crop model coverage
Extend specialist models across more crops and climates
Validator scoring framework
Score forecasts against measured harvest outcomes
Crowdloan & subnet registration
Fill the crowdloan, register the leased subnet, go live
P. Andersson
founder · agronomy + ML
L. Chen
data & pipelines
O. Baptiste
model training
Forecast pipeline running
Our pilot pipeline now turns live sensor feeds into yield forecasts end to end. Multi-crop coverage is the next milestone.
First regional dataset cleaned
Labeled sensor and harvest data for a first growing region is indexed and ready for training.
Crowdloan opened
The Cropmind crowdloan is live. Backers who lock TAO now receive pro-rata lease shares at graduation.