DeepLeaf: End-to-End Crop Health Management

Late and inaccurate detection of crop diseases, pests, and nutrient stress leads to $300B in annual global losses, with 40% crop losses in Africa and Asia. 80% of smallholders lack access to expert agronomic advice. Current solutions are fragmented and reactive: satellite companies show indices but stop there, IoT solutions cost $2,500+ per site and do not scale, and agronomists are expensive and not always available. Farmers spray entire fields uniformly, wasting chemicals with no guidance on treatment timing or residue management. DeepLeaf AI enables early, accurate, and scalable crop health diagnosis using AI-powered image analysis, satellite monitoring, and expert knowledge systems—providing full accompaniment from planning to certified, residue-free harvest.

DeepLeaf is an agritech company developing AI-driven solutions for early detection and management of crop health risks. Its software uses computer vision and machine learning models trained on large-scale plant image datasets to identify diseases, pests, and nutrient deficiencies across diverse crops. The platform provides end-to-end farm management from planning to certified harvest, using satellite imagery (Sentinel-1/2), weather data, and AI-powered diagnostics. DeepLeaf serves farmers of all scales—from smallholders to large commercial operations—through accessible channels including WhatsApp, USSD, mobile apps, and web dashboards. The company focuses on reducing chemical inputs by 60-80% through precision agriculture while ensuring zero residues at harvest through automated pre-harvest interval compliance.