See rice production
before it reaches the market.

Cropin AI models use proprietary crop knowledge grid, satellite data, and weather forecasts to guide farmers on optimal water usage. The platform recommends when and how much to irrigate, helping reduce water wastage while ensuring healthy crop growth, even in water-scarce regions.

Growth index analysis per plot involves tracking crop health and growth at the individual field level using satellite imagery and AI. By monitoring each plot, Cropin identifies underperforming areas, predicts yields, and suggests timely interventions, allowing farmers to make precise, data-driven decisions.

Cropin combines Geographic Information System (GIS) mapping with remote sensing data to detect stress patterns in rice fields that may indicate pest infestation. This allows farmers to identify hotspots early, target pest control measures efficiently, and prevent large-scale outbreaks. Cropin Disease Early Warning System (DEWS) provides alerts on probablity of disease occurrence to implement mitigative steps.

Cropin’s DEWS monitors key rice diseases and pests, including: Bacterial blight, Sheath blight, Rice blast, Brown spot, Brown planthopper. The system provides early alerts and management recommendations, reducing crop loss and chemical overuse.

Cropin analyzes soil health, nutrient levels, and historical crop data to recommend targeted interventions like crop rotation, organic amendments, and optimized fertilization. This approach restores soil fertility, improves long-term yields, and ensures sustainable rice cultivation.

Using the Space4Good collaboration as a benchmark, Cropin utilizes radar and optical satellite imagery to identify rice plots even through cloud cover. This is critical for rice, as it is often grown during monsoon seasons when traditional satellite visibility is low.

Rice cultivation is a major source of methane emissions. Cropin enables the monitoring of “Alternate Wetting and Drying” (AWD) techniques. By digitizing water management logs and verifying field conditions via satellite, the platform provides the “Evidence” needed for carbon credit certification and sustainable rice labels.

Cropin uses satellite intelligence to detect the exact date of transplanting across thousands of hectares. This allows companies to precisely calculate the crop’s lifecycle and predict harvest dates with high accuracy, optimizing the procurement window for millers.

Yes. By integrating historical weather patterns with real-time flood monitoring, the platform can estimate potential yield losses during a flood event and adjust final output forecasts. This helps rice exporters and government agencies to proactively manage food security risks.

Direct Seeded Rice (DSR) is a more water-efficient method than traditional puddling. Cropin provides field officers with digital workflows to guide farmers through the specific “Package of Practices” (PoP) required for DSR, ensuring correct seed depth and weed management to maximize the variety’s potential.

Cropin combines satellite-derived evapotranspiration data with pincode-level weather data to calculate the water productivity of rice crops. This allows organizations to identify which clusters are using water most efficiently and where irrigation interventions are needed.

The platform’s “Disease Early Warning System” alerts agents when growth stage, temperature, and humidity levels reach the threshold for BPH or Rice Blast. Agents can then send localized “In-App” advisories to farmers to take preventive action before the pest destroys the crop.