This is like giving farmers a smart pair of binoculars and ears that constantly watch and listen to their fields, spotting bugs and diseases long before a human would notice and telling them exactly where to act.
Farmers often detect pests and crop diseases too late, leading to major yield losses and overuse of chemicals. Continuous AI monitoring can spot early signs of infestation or disease and guide targeted interventions, reducing waste and protecting harvests.
Access to large, labeled agronomic datasets (images and sensor data across crops, geographies, and seasons), plus tight integration into growers’ existing equipment and farm-management workflows can create strong switching costs and continuous model improvement.
Hybrid
Vector Search
High (Custom Models/Infra)
Model accuracy and robustness across many crops, climates, and imaging conditions, plus edge-device compute limits and connectivity in remote fields.
Early Adopters
Positioned as a transformational, AI-driven scouting tool that detects problems earlier and more consistently than manual field walks, and can be deployed at scale across large acreages.