Normalized claim
Quantified impact: 30% increase
Increased crop yields by 30%
Last evidence check: Jul 22, 2026
Farmers in India significantly increase yields using AI-driven solutions
Use case typeCrop yield predictionUpdated Jun 13, 2026
Microsoft collaborated with ICRISAT to develop an AI Sowing App and Pest Risk Prediction API to address challenges in farming caused by irregular rainfall and pest attacks. Participating farmers received sowing advisories and pest risk alerts via SMS, enabling optimized sowing and pest control based on predictive insights. The project benefited over 3,000 farmers, improving crop yields by 10%-30% and minimizing irrigation wastage. Advanced models analyzed long-term weather patterns and soil moisture indexes to calculate optimal sowing times, while the Pest Risk Prediction API proactively warned of potential pest attacks.
- Organization
- Small farmers in Andhra Pradesh and Karnataka
- Industry
- Agriculture
- Location
- India
- Published
- November 2017
Reported outcomes
+30%
quantified impactOther quantified impact
Strategic outcomes
New product / capabilityDeveloped AI sowing and pest prediction toolsCustomer experience & trustDelivered personalized farming advisories and alertsBetter decisions & insightEnabled optimal sowing and pest control decisionsScale & capacityImproved farming practices for thousands of farmers
Why do we believe this?Outcome claims, sources, and evidence checks
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Small farmers in Andhra Pradesh and Karnataka
- Provider
- Microsoft
- Maturity
- Unknown
- Linked source
- Microsoft News
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1Yield optimization
- 2Pest attack prediction
- Irregular rainfall leading to poor crop yield
- Lack of modern tools to predict optimal sowing times
- High vulnerability to pest attacks
- Limited accessibility to advanced technologies for small farmers
- Increased crop yields by 30%
- Improved farming practices for over 3,000 farmers
- Reduction in irrigation wastage
- Support for policy makers with commodity price forecasting models
Architecture
The AI Sowing App utilizes Cortana Intelligence Suite for machine learning insights on optimal sowing periods, while the Pest Risk Prediction API leverages predictive analytics for pest attack mitigation based on weather and crop stage data.
Sources & evidence1
Evidence: Medium60/100Evidence strength
- Customer explicitly identified
- Independent source available
- Quantified outcome available
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jul 22, 2026.
Live sourceStill referenced
The case's original source is still reachable.
- Cited source last checked Jun 12, 2026 — ok (0/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
Type: News ArticlePublished: Nov 7, 2017Publisher: Microsoft NewsEvidence: SecondaryConfidence: Low
AI-generated summary. Verify important details with the linked sources before relying on this case.
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