The Challenge
For many smallholder farmers in India, pests and diseases pose a critical threat to income stability, but often go undetected due to subtle symptoms and the limited reach of rural extension services.
Regional variation in crop varieties and heavy reliance on inconsistent, informal advice frequently leads to excessive pesticide use, causing crop damage and unsafe chemical practices for those with the least support.
Our AI Solution
CropAce is a vision-led AI application engineered to identify crop pests and diseases directly from field images, providing grounded recommendations for timely action.
Built for the realities of Indian agriculture, the application performs reliably in challenging field conditions—low lighting, varying camera quality, and noisy, diverse backgrounds.
How it works
01
Capture symptom image
A farmer or field worker captures an image of an affected leaf, stem, canopy, or pest symptom on a mobile device.
Capture symptom image
A farmer or field worker captures an image of an affected leaf, stem, canopy, or pest symptom on a mobile device.
02
Vision model analysis
The image is analyzed by a vision model trained on a diverse dataset of crop images collected from Indian farms, optimized for real-world field variability.
Vision model analysis
The image is analyzed by a vision model trained on a diverse dataset of crop images collected from Indian farms, optimized for real-world field variability.
03
Identify likely threat
The application identifies the likely threat, distinguishing between pest types, nutrient deficiencies, diseases, and non-threatening conditions.
Identify likely threat
The application identifies the likely threat, distinguishing between pest types, nutrient deficiencies, diseases, and non-threatening conditions.
04
Human-in-the-loop validation
expert review loops validate and refine labels, improving detection accuracy and reducing misclassification risk.
Human-in-the-loop validation
expert review loops validate and refine labels, improving detection accuracy and reducing misclassification risk.
05
Actionable guidance
Actionable guidance is generated, offering a timely recommended action and links to localized extension protocols.
Actionable guidance
Actionable guidance is generated, offering a timely recommended action and links to localized extension protocols.
06
Visibility for extension teams
Extension teams gain visibility, as aggregated data helps departments and organizations see where outbreaks may be emerging.
Visibility for extension teams
Extension teams gain visibility, as aggregated data helps departments and organizations see where outbreaks may be emerging.
Where It's Deployed
Deployed in Gujarat, Maharashtra, Madhya Pradesh, Rajasthan.
Impact
CropAce is built to support farmers (early detection, safer and more targeted pesticide use, reduced dependency on informal advice, faster decisions that reduce crop loss), extension workers (consistent diagnostic support, faster triage, less manual identification work), farmer groups & FPOs (collective risk awareness, better input planning), and state agriculture departments (early warning signals for outbreaks, more consistent advisory delivery, better intervention planning). It works on low-end smartphone cameras and unstable connectivity.
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Looking Ahead
Ahead of its 2026 launch, CropAce is being expanded to cover four crops and 40+ pest-and-disease combinations, with continued human-in-the-loop validation to strengthen detection accuracy at scale.