One organizational platform. A complete loop from field sensors to every farmer's phone.
Drone multispectral imaging + IoT soil/weather sensors. Raw imagery + time-series sensor data.
CNN vision models + time-series ML forecasting. Disease maps, irrigation need, yield forecast.
Organization dashboard for your team + mobile app/SMS as the delivery layer to every farmer.
Variable-rate sprayers/irrigation + field crew logs. Executed treatment & outcome data.
Early spectral signatures identified across 20+ bands. Outbreaks flagged 7–14 days before visible symptoms. Geo-tagged severity zones guide treatment prioritization.
Zone-specific watering schedules updated continuously. Fuses soil moisture, weather forecasts, and crop-stage data. Compatible with variable-rate irrigation infrastructure.
Sub-field projections updated continuously through the season. Improves harvest logistics, storage planning, and forward contracting decisions.
Nutrient deficiency maps from multispectral imagery. Integrates with variable-rate fertilization equipment. Reduces input overuse by 10–20%.
Field crew alerts ranked by severity and zone. Push notifications to SMS and mobile app. Zero desk time required for basic operations.
Comprehensive field maps across your whole network. Treatment history and outcome logs. Automated ROI tracking vs control blocks, rolled up by region or branch.
Agribusinesses and system integrators can call CropNexa's detection, irrigation, and forecasting models directly, embedding field intelligence into their own existing software.
Deploy our ruggedized IoT nodes across strategic field zones in a single day.
Connect existing historical yield data, weather station feeds, and machinery logs.
Initial multispectral drone survey to map field topography and baseline crop health.
Our localized AI begins analyzing streams and generating baseline forecasts.
Receive daily insights, predictive alerts, and variable-rate prescription maps.
| Metric | Before CropNexa | With CropNexa |
|---|---|---|
| Disease detection lead time | At symptom onset | 7–14 days earlier |
| Water use per hectare | Fixed schedule | 15–30% reduction |
| Fertilizer/input cost | Uniform application | 10–20% reduction |
| Yield per hectare | Historical average | 8–20% improvement |
| Scouting labor hours | Full manual coverage | 40–60% reduction |
Four integrated layers convert raw field data into actionable decisions — continuously and automatically.
Multispectral and RGB imagery from drones and/or satellite feeds, combined with ground-based IoT sensors for soil moisture, soil nutrients, temperature, and humidity. This layer ensures 100% field coverage at the resolution and frequency required to detect problems before they become losses.
Computer vision models detect disease lesions, pest damage, nutrient deficiency, and canopy stress from imagery; time-series ML models fuse sensor and weather data to predict irrigation need and forecast yield. All models run on NVIDIA-accelerated infrastructure via AWS SageMaker for low-latency inference at scale.
Your organization's team gets a command dashboard across every member farm; each individual farmer gets the CropNexa mobile app and SMS alerts — the delivery layer your cooperative, agribusiness, or NGO program puts directly in their hands, at no extra cost to the farmer. Alerts are ranked by severity and zone so field crews and farmers always know what to address first.
Recommendations are executed via variable-rate irrigation/spray equipment where available, or manually by field crews. Outcomes are logged and fed back into the models to improve accuracy over time — meaning CropNexa becomes smarter every season on your specific fields.
| Layer | Key Technology | Primary Output |
|---|---|---|
| Data Capture | Drone multispectral imaging, IoT soil/weather sensors | Raw imagery & time-series sensor data |
| AI Processing | CNN-based vision models, time-series ML forecasting | Disease maps, irrigation need, yield forecast |
| Decision & Alerting | Cloud dashboard, mobile app, SMS alerts | Prioritized field alerts & recommendations |
| Action & Feedback | Variable-rate sprayers/irrigation, field crew logs | Executed treatment & outcome data |
Table 2. Solution architecture layers, technologies, and outputs.
Computer vision models trained on multispectral drone imagery identify early spectral signatures of disease and pest stress that are invisible to the naked eye, often days to weeks before visible symptoms appear. Detected anomalies are geo-tagged and ranked by severity so scouting and treatment can be prioritized to the specific sub-field zones affected rather than the entire field.
Soil moisture sensors combined with weather forecasts and crop-stage models generate zone-specific irrigation recommendations, reducing both water waste and drought stress. Where variable-rate irrigation infrastructure exists, recommendations can be applied automatically; otherwise they are delivered as actionable schedules to field staff.
Historical yield data, current-season imagery, and weather patterns are fed into regression and time-series models to produce continuously updated yield forecasts at the field and sub-field level, improving harvest logistics, storage planning, and forward contracting decisions.
Nutrient deficiency maps derived from imagery inform variable-rate fertilizer application, targeting inputs to the zones that need them rather than applying a uniform rate across the whole field. Integrates directly with John Deere, Valley, and other major variable-rate equipment APIs.
Command & Control
The CropNexa command dashboard gives agronomists and farm managers a single pane of glass across all field zones — live sensor readings, AI-generated disease risk maps, irrigation status, and yield forecasts updated daily.
Alerts are ranked by severity and economic impact so your team always knows exactly where to focus. No more guessing. No more driving the whole farm to check on a hunch.