Sarlaben AI App Brings Cattle Care to India’s Dairy Farmers

09 September 2026, New Delhi: Artificial intelligence is moving from laboratories and technology centres into India’s villages, with a new application called Sarlaben emerging as an example of how AI can be deployed at scale to support farmers and the livestock sector.

The AI-powered assistant, developed for Amul’s dairy cooperative network, is designed to provide farmers with real-time, personalised information on cattle health, feeding, breeding, milk production and related agricultural and government services. The application is already being used by millions of dairy producers in Gujarat, with women accounting for a significant share of its users.

The application gained international attention during the India AI Impact Summit 2026, when Infosys co-founder Nandan Nilekani used Sarlaben as an example of the speed at which artificial intelligence can move from an idea to a large-scale rural application.

Nilekani said that when he met Prime Minister Narendra Modi on January 8 to discuss the use of AI for farmers, Modi asked why similar technology could not be applied to cattle. The Prime Minister pointed out that while a farmer can describe a problem, an animal cannot communicate when it is sick. That discussion led to an effort to develop an AI-based solution for the dairy sector. According to Nilekani, the application went live on February 11 — roughly three weeks after the January meeting.

From farmer advice to cattle intelligence

Sarlaben is designed around a relatively simple proposition: give dairy farmers access to useful information when they need it, rather than requiring them to depend entirely on physical veterinary visits or other intermediaries.

Farmers can use the system to seek guidance relating to their cattle, including health problems, pregnancy, breeding, feed and milk production. The application provides information in local languages, making it more accessible to farmers who may not be comfortable using English-language digital services.

For India’s dairy sector, the potential significance is substantial. Amul’s cooperative network represents approximately 3.6 million milk producers, around 40 million cattle and about 2 billion milk transactions annually, according to figures cited by Nilekani during the summit.

This scale gives the project a particularly important agricultural dimension. Rather than treating AI as a standalone technology product, Sarlaben is being integrated into an existing cooperative system that already has relationships with farmers, veterinarians and milk collection networks.

Using India’s agricultural data

One of the distinctive features of the initiative is its reliance on the large body of operational data accumulated by the cooperative ecosystem.

Information generated through milk procurement, veterinary services, breeding and cattle management can potentially help AI systems provide more context-specific responses. Nilekani also highlighted the importance of keeping Amul’s data within India and maintaining control of the cooperative’s data infrastructure.

That approach could become increasingly important as agricultural AI expands. Farmers require advice that reflects local conditions — from animal breeds and feed availability to weather, disease patterns and farming practices. AI systems connected to reliable local datasets have the potential to provide more relevant assistance than generic digital information sources.

Why livestock matters to agricultural AI

The Sarlaben example also broadens the definition of AI in agriculture.

Much of the global discussion around agricultural AI has focused on crop monitoring, precision spraying, satellite imagery, weather forecasting and autonomous machinery. Livestock, however, presents another major opportunity.

Early identification of animal health problems can potentially reduce losses, improve productivity and allow farmers to seek veterinary intervention sooner. Better information on breeding and nutrition can also support herd management and milk production.

For small dairy producers, particularly those with limited access to veterinary services, an always-available digital assistant could become an important first point of information.

Prime Minister Modi subsequently cited Sarlaben as an example of AI being used for grassroots impact, alongside other Indian agricultural AI initiatives. The Indian government has presented the application as part of a broader effort to make AI accessible and useful to ordinary citizens, particularly in rural communities.

A model for rural AI adoption

The speed with which Sarlaben moved from an idea discussed on January 8 to a live application on February 11 was the central point in Nilekani’s presentation at the AI Impact Summit.

For India, the project represents more than a new technology application for dairy farmers. It illustrates a model in which government vision, a large agricultural cooperative, technology organisations and existing rural data infrastructure can come together to deploy AI rapidly.

The larger question now is whether similar models can be extended beyond cattle health and dairy production to other areas of agriculture — including crop advisory, pest and disease management, irrigation, market intelligence, weather-related decisions and access to government programmes.

India is already pursuing that broader direction. At the AI Impact Summit, the government highlighted Bharat VISTAAR, a multilingual AI platform intended to provide farmers with information covering areas such as weather and market prices.

Sarlaben therefore offers an early glimpse of what AI-driven rural services could look like when they are delivered not simply as consumer technology, but through agricultural institutions that already reach millions of farmers.

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