Amul’s Sarlaben: AI Transforming Dairy 🐄🚀
AI
🎧
In the villages of Gujarat, India, Amul dairy farming is experiencing a significant shift. Thirty-six lakh women milk producers are utilizing an AI assistant named Sarlaben. Amul, the world’s largest dairy cooperative, has introduced Amul AI, leveraging fifty years of cooperative data to provide personalized guidance in their local languages. Launched prior to India’s AI Impact Summit 2026 and supported by the Ministry of Electronics and Information Technology, the system integrates with Amul’s Automatic Milk Collection System and the Pashudhan application. The platform utilizes data from over ten lakh mobile app users, veterinary records from 1,200 doctors, ISRO satellite imagery, and a five-yearly cattle census. This represents a substantial investment in India’s largest dairy sector, which produced 347.87 million tonnes of milk in 2024-25, demonstrating the nation's position as a global leader in dairy production.
AMUL AI: A VILLAGE-LEVEL AI REVOLUTION
Amul, the world’s largest dairy cooperative, is pioneering a groundbreaking deployment of artificial intelligence – not in a research lab, but directly within the villages of Gujarat, India. This initiative, dubbed Amul AI, is being implemented to assist 36 lakh (3.6 million) women milk producers, representing a significant test case for the potential of AI to reach underserved communities. The project is backed by the Ministry of Electronics and Information Technology (MeitY) and the EkStep Foundation, highlighting its national importance.
Sarlaben: The Personalized Dairy Assistant
The core of Amul AI is Sarlaben, an AI assistant designed specifically for dairy farming. Sarlaben leverages one of India’s most extensive agricultural data repositories, accessible through the Amul Farmer mobile app (downloaded by over 10 lakh users) and via voice calls for farmers utilizing feature phones or landlines. This ensures that farmers receive immediate, relevant guidance regardless of their technological access.
A Data Foundation of Unprecedented Scale
What distinguishes Amul AI is the sheer volume and depth of its training data. The platform is built upon a digital backbone managing over 200 crore (two billion) milk procurement transactions annually. This data is supplemented by veterinary treatment records from over 1,200 doctors covering nearly 3 crore (30 million) cattle, approximately 70 lakh (seven million) artificial inseminations conducted each year, and ISRO satellite imagery for precise fodder production mapping. Each animal within the system is uniquely identified, with detailed records of feed intake, disease history, and milking status, creating a truly holistic picture of each animal’s needs.
Bridging the Information Gap
Jayen Mehta, Managing Director of the Gujarat Cooperative Milk Marketing Federation (GCMMF), emphasizes the core mission of Amul AI: “It’s about taking dependable, verified information directly to the farmer – instantly and in a language they are comfortable with.” This directly addresses a long-standing bottleneck in the Indian dairy sector – the lack of timely information, particularly for farmers facing challenges in remote villages.
India’s Dairy Productivity Paradox
Despite India’s position as the world’s largest milk producer (generating 347.87 million tonnes in 2024-25, more than double the US’s 102.70 million tonnes), India’s per-animal milk yield remains among the lowest globally. This disparity stems from several structural issues: small herd sizes, reliance on low-quality feed, limited access to veterinary care in rural areas, and a general lack of awareness regarding modern breeding and husbandry practices. Amul’s extensive network, spanning over 18,600 villages in Gujarat, where farmers supply over 350 lakh litres (35 million litres) of milk daily, highlights the scale of this challenge.
Vernacular AI and the Potential for “White Revolution 2.0”
The success of Amul AI hinges on addressing information asymmetry. Farmers facing a sick animal at midnight in a remote village have historically had few resources. Sreeshankar Nair, Founder of Brainwired, identifies three key areas where Amul AI can make a substantial impact: farmer awareness, access to quality veterinary guidance, and connectivity to grazing and feed resources. Nair believes that if AI can integrate local dialects of Indian languages, India can achieve “White Revolution 2.0,” a second wave of dairy expansion driven by accessible, localized technology.
The Cooperative Model: A Data-Rich Ecosystem
The technological story of Amul AI is inextricably linked to the cooperative model itself. Amul’s cooperative structure, built over five decades under the original White Revolution, created the foundational data infrastructure that makes Amul AI possible. Unlike most private agri-tech startups that collect data first and then build products, Amul already possessed this wealth of information. The challenge was to translate it into actionable insights for farmers.
Multilingual Accessibility and National Reach
Initially available in Gujarati – the primary language of the cooperative’s farmer base – the Amul AI platform is built on the government’s Bhashini multilingual framework. This framework has the potential to extend the platform’s reach to 20 Indian languages, encompassing Amul’s presence in 20,000 villages across 20 states. This ambitious expansion underscores the government's commitment to leveraging AI for rural development.
Institutional Roots and the IRMA Perspective
Saswata Narayan Biswas, Director of the Institute of Rural Management, Anand (IRMA) – the institution closely associated with Amul’s founding ethos – frames the project as a continuation of the cooperative’s commitment to innovation and farmer empowerment. The success of Amul AI represents a crucial step in applying technological advancements to address the specific challenges of India’s dairy sector, reinforcing the importance of data-driven decision-making and collaborative solutions.
This article is AI-synthesized from public sources and may not reflect original reporting.