AI dairy farming has discovered its most formidable deployment but – not in a Silicon Valley lab nor a European agri-tech campus, however within the villages of Gujarat, India, the place 36 lakh (3.6 million) girls milk producers are actually being served by an AI assistant named Sarlaben.
Amul, the world’s largest dairy cooperative, has launched what it calls Amul AI: a platform constructed on 5 many years of cooperative information, designed to offer each farmer in its community round the clock, personalised steerage in their very own language.
Amul was launched simply forward of India’s AI Influence Summit 2026 and backed by the Ministry of Electronics and Data Expertise (MeitY) with the EkStep Basis. It’s a check case for whether or not AI – the sort being debated in boardrooms and coverage boards globally – can truly attain the final mile.
Meet Sarlaben: The AI dairy farming assistant
Sarlaben attracts from one in all India’s most complete agricultural information repositories. It’s accessible by way of the Amul Farmer cellular app – already downloaded by over 10 lakh (a million) customers on Android and iOS – in addition to by means of voice requires farmers utilizing characteristic telephones or landlines.
The system is built-in with Amul’s Computerized Milk Assortment System (AMCS) and the Pashudhan utility, permitting it to supply personalised, cattle-specific steerage.
What makes Amul AI considerably completely different from most agricultural chatbots is the dimensions of its coaching information. The platform was constructed on a digital spine managing over 200 crore (two billion) milk procurement transactions yearly, veterinary remedy information from greater than 1,200 medical doctors overlaying practically 3 crore (30 million) cattle, roughly 70 lakh (seven million) synthetic inseminations performed every year, ISRO satellite tv for pc imagery for fodder manufacturing mapping, and a cattle census performed each 5 years.
Each animal within the system carries a singular ID, with particular person information of feed consumption, illness historical past and milking standing. “Amul AI is about taking reliable, verified info on to the farmer – immediately and in a language they’re comfy with,” mentioned Jayen Mehta, Managing Director of the Gujarat Cooperative Milk Marketing Federation (GCMMF), which markets the Amul model.
He mentioned how, by utilizing many years of structured information and integrating it with their operational techniques, the platform will assist farmers make well timed choices that enhance animal productiveness and revenue.
India’s productiveness paradox
India is the world’s largest producer of milk, producing 347.87 million tonnes in 2024-25 in keeping with the Division of Animal Husbandry and Dairying – greater than double the US’s 102.70 million tonnes. And but regardless of main in quantity, India’s per-animal milk yield stays among the many lowest globally.
The explanations are structural. India’s dairy sector is characterised by small herd sizes, low-quality feed, restricted entry to veterinary care in rural areas, and widespread lack of knowledge about trendy breeding and husbandry practices. Amul’s community spans greater than 18,600 villages in Gujarat, the place farmers provide over 350 lakh litres (35 million litres) of milk each day.
However info asymmetry has lengthy been a bottleneck – a farmer dealing with a sick animal at midnight in a distant village has few locations to show; the hole Amul AI is designed to shut.
Out there initially in Gujarati – the first language of the cooperative’s farmer base – the platform is constructed on the federal government’s Bhashini multilingual framework and will, in precept, be prolonged to twenty Indian languages, reaching Amul’s presence in 20,000 villages in 20 states.
The cooperative mannequin
The know-how story right here is inseparable from the institutional one. Amul’s cooperative construction – constructed over 5 many years underneath the unique White Revolution – created the information infrastructure that makes Amul AI doable.
Most personal agri-tech startups are working backwards: accumulating information first, constructing merchandise second. Amul already had the information. What was wanted was a solution to make it actionable on the farmer degree.
Specialists monitoring the dairy-tech house see this as vital. Sreeshankar Nair, Founding father of Brainwired, a dairy-tech startup, identifies three particular challenges that Amul AI might meaningfully tackle: farmer consciousness, entry to high quality veterinary steerage, and connectivity to grazing and feed sources.
“If AI can combine native dialects of Indian languages, India can have White Revolution 2.0,” Nair mentioned, pointing to the transformative potential of vernacular AI in a sector the place not each farmer speaks the identical dialect.
Saswata Narayan Biswas, Director of the Institute of Rural Administration, Anand (IRMA) – the establishment intently related to Amul’s founding ethos – frames it as an AI embedded in a cooperative framework. It turns into “not a know-how improve, however an instrument of inclusive rural transformation.”
For Biswas, the precise talents Amul AI brings – predictive illness detection, oestrus monitoring, optimised feed formulation, localised climate threat advisories – are talents Amul had been constructing for years. AI accelerates and democratises them.
Scale and the check forward
The launch has drawn backing from the very best ranges of presidency. Gujarat Chief Minister Bhupendra Patel launched the platform and confirmed it is going to be showcased on the AI Influence Summit 2026. The cooperative has acknowledged MeitY and the EkStep Basis – an open digital infrastructure nonprofit – as companions in constructing the AI layer.
Farmers not affiliated with Amul may entry normal dairying and animal husbandry info by means of the app. At its present scale, Amul AI already covers extra cattle – practically 3 crore (30 million) – than most nationwide veterinary databases anyplace on the earth.
The more durable query, as with most AI deployments at a inhabitants scale, is whether or not the device will serve those that want it most. The farmers almost certainly to learn first – these already comfy with smartphones, already plugged into Amul’s digital system – might not be those with the best info deficit.
The rollout of Bhashini-enabled dialect help, the adoption charge amongst feature-phone customers counting on voice calls, and whether or not AI-driven advisories translate into measurable yield enhancements would be the metrics that decide whether or not that is genuinely White Revolution 2.0.
Amul has constructed an AI system grounded in half a century of actual cooperative transactions, actual animals, and actual farmers. Such an infrastructure is, arguably, essentially the most credible basis for AI dairy farming at scale. Whether or not it fulfils its promise will rely upon execution – and on whether or not Sarlaben’s voice can attain in the previous few miles; those who have all the time been the toughest to cross.
See additionally: Hitachi bets on industrial experience to win the bodily AI race
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