Greenalytics provides farms with hyperspectral imaging and AI-driven analytics to monitor field conditions in real time. Its platform delivers satellite-based vegetation health maps, early warnings for stress and disease, and precise yield forecasts, enabling growers to schedule irrigation, inputs, and interventions with data-backed confidence. Users receive automated reports and smart alerts that translate complex sensor data into actionable recommendations tailored to each crop and location.
Funding
Funding not disclosed
Founders
Product
Problem
Farmers often lack timely, detailed information about crop health, making it difficult to detect stress, disease, or water deficiencies before they impact yields. Traditional monitoring relies on periodic field visits or low‑resolution imagery, which can miss early warning signs and lead to inefficient input use.
Solution
Greenalytics combines hyperspectral satellite imaging with AI-driven analytics to provide continuous, high‑resolution visibility of field conditions. The platform processes spectral data to identify subtle changes in vegetation health, enabling detection of stress and disease days before visual symptoms appear. Real‑time alerts and actionable recommendations are delivered in plain language, guiding irrigation, pest control, and input timing. Historical benchmarks and AI‑powered yield forecasts help growers plan and optimize future planting cycles. The system adapts to specific crops, locations, and management practices, ensuring that insights are tailored to each farm’s operational goals.
Target Audience
Primary customers are commercial and large‑scale growers, agronomists, and farm management companies seeking data‑driven tools to improve crop health monitoring and input efficiency.
Features
- Live hyperspectral satellite monitoring of vegetation health, biomass potential, and water saturation with sub‑field precision
- Early warning engine that flags stress and disease indicators days in advance of visual symptoms
- AI-generated disease detection and treatment recommendations based on integrated crop, soil, and environmental data
- Automated plain‑language alerts for irrigation scheduling, disease risk, and input application timing
- Historical benchmark comparison and AI‑driven yield forecasting for strategic planning
- Customizable dashboards that visualize current conditions alongside multi‑year satellite and environmental history