Normalized claim
Quantified impact: 21-40%
Yield increases of 21-40% for participating farmers.
ITC, a large multi-business company in India, partnered with Microsoft to develop the Krishi Mitra app—an agricultural super app—using Microsoft Copilot, Azure Data Manager for Agriculture, and AI technologies. The app provides farmers with personalized guidance on crop management, pest control, soil health, and water conservation using generative AI and Natural Language Processing, supporting multiple local languages. FarmBeats research has been operationalized in real deployments, and Microsoft also supports Baramati Agricultural Development Trust (ADT) to reach sugarcane farmers with AI, sensors, and satellite data. The solution enables contextual advice via smartphones, integrating weather, market pricing, and agronomic data, thus overcoming traditional barriers of connectivity and expertise for smallholder farmers. Through orchestration plugins, Semantic Kernel, and RAG techniques, Krishi Mitra ensures accurate, relevant responses and data-driven decision support. Projects have scaled to thousands of farmers, with anticipated growth to 10 million by 2030, aiding India's workforce in the face of climate, pest, and sustainability challenges. AI tools continuously evolve and improve recommendations; real-time insights help optimize irrigation scheduling, harvest timing, and pesticide application for better yield and profit. The initiative supports India's agricultural sector, which sustains 43% of the workforce, breaks down language barriers, and improves digital adoption among rural communities. Overall, Microsoft technology has empowered farmers to adopt more sustainable, profitable, and resilient farming models via direct access to time-sensitive, localized data.
Reported outcomes
21-40%
quantified impactOther quantified impact
Strategic outcomes
Normalized claim
Quantified impact: 21-40%
Yield increases of 21-40% for participating farmers.
Normalized claim
Quantified impact: 5-9% decrease
Reduction in pesticide and fertilizer usage by 5-9%.
Normalized claim
Time: 30% decrease
Lowered irrigation time and input costs by up to 30%.
Projects have scaled to thousands of farmers, with anticipated growth to 10 million by 2030, aiding India's workforce in the face of climate, pest, and sustainability challenges
Primary read
Showing 3 of 5
Krishi Mitra uses Semantic Kernel-based orchestration to route queries to Microsoft plugins, which retrieve real-time weather, market, and agronomic data. Azure Data Manager for Agriculture aggregates diverse farm datasets. The app layers generative AI (Copilot) for natural language chat and retrieval-augmented generation (RAG) for contextual answers. IoT sensors and satellite data flow into backend Azure services and are analyzed by AI to power mobile advisory and alerts.
The same organization appears in newer AI deployment evidence.
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
Was this useful?
Community
No published comments yet.