Earn the trust of farmers for AI diffusion across farms

Last week, Amul launched Sarlaben, an AI-powered digital assistant for dairy farmers in Gujarat.

- SHANKAR MARUWADA

It will benefit over 3.6 million milk producers, most of them women, across more than 18,500 villages. Sarlaben answers queries on dairy farming, animal husbandry and milk procurement in real time, and is accessible through the Amul Farmer mobile app and via voice calls in Gujarati by those using basic feature phones.The challenges were remarkable. The system must be able to understand farmers speaking Gujarati and local dialects, work amid intermittent connectivity in rural areas and give advice they can stake their livelihoods on. It draws from over 50 years of verified cooperative data, including 2 billion milk procurement transactions annually, veterinary treatment records of 30 million cattle and farmer-wise cattle census data.

Maharashtra's Vistaar agricultural advisory system took nine months from commitment to deployment in 2025. The state wanted AI-powered advice for farmers in Marathi and local dialects, accessible via basic phones and available even when connectivity drops during the monsoon season. Ethiopia's OpenAgriNet took three months to deploy earlier this year, addressing the same core challenge of agricultural advice at scale, but with a pathway already mapped by Maha Vistaar.

Amul's Sarlaben took just three weeks. This time compression happened because deployment know-how became transferable. The technical architecture, governance frameworks, evaluation protocols and deployment playbooks that took nine months to build for a pioneer like Maharashtra could be reused and adapted rather than rebuilt from scratch.