Tech giant is expanding its AI push in India across two different landscapes, farm fields and cultural heritage, but both share a common goal of harnessing data to deliver locally relevant insights.
The company unveiled two developments showcasing its focus in these areas, building on its research expertise.
On the agricultural front, Google DeepMind and its Partnerships Innovation team have rolled out the Agricultural Monitoring & Event Detection API (AMED API). Building on the Agricultural Landscape Understanding API (ALU API), which uses satellite imagery and AI to map field boundaries and land use across India. The AMED API drills down to the level of individual plots.
Through this interface (API, or application programming interface), developers can query: crop type and season, field size, and three‑year activity history.
With updates roughly every two weeks, the AMED API can offer farmers and agritech partners timely data to fine‑tune irrigation schedules, assess soil requirements, or even forecast yields.
As Alok Talekar, Lead, Agriculture and Sustainability Research Lead, Google DeepMind, noted, “Our commitment to the sustainable growth of India’s agricultural sector deepens with every innovation. With AI research—and especially with AMED building on the foundation of ALU—we’re working on accelerating crucial shifts, transforming broad insights to granular, real‑time data, so that increasingly impactful solutions not only translate into benefit for India’s farmers, but also bolster the nation against rising climate risks.”
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One early adopter, TerraStack (incubated at IIT‑Bombay), uses the ALU API to power a rural land intelligence system. By automatically detecting farm boundaries and changes, such as encroachment or shifts in ownership, it helps organisations modernise land records and assess climate vulnerability, streamlining lending and support for millions of smallholders.
“These APIs are helping standardise and transform previously unorganised and unusable data into solutions for one of India’s most critical sectors,” remarked TerraStack’s co-founder and CEO, Aaryan Dangi.
Meanwhile, Google’s “Amplify Initiative” is tackling another kind of ground: India’s staggering linguistic and cultural diversity.
Large Language Models (LLMs) often stumble when faced with local dialects or region‑specific terminology. To bridge that gap, Google and IIT‑Kharagpur have partnered. The idea is to assemble hyperlocal datasets covering health, safety and other community‑vital topics in multiple Indic languages.
Field experts feed information and phrases into privacy‑preserving mobile and web apps; regional partners then translate, vet and annotate the content, carefully watching for bias and natural fluency.
This isn’t Google’s first foray into Indic language AI. Three years ago, it launched Project Vaani with the Indian Institute of Science. This opened up over 21,500 hours of speech audio and 835 hours of transcriptions across 86 languages via India’s Bhashini mission. That corpus is now freely available to developers building voice‑powered tools, from digital assistants to accessibility services.
“AI models can be even more helpful with a deeper understanding of the vastness and complexity of the lived human experience,” explained Madhurima Maji, Lead Program Manager, Amplify Initiative for India at Google. “Through the Amplify Initiative, we are meticulously building the rich, hyperlocal context and cultural understanding that transforms raw information into profound knowledge.”
Partha Talukdar, Language Research Lead at Google DeepMind, underscores the broader vision, “We’re committed to ensuring that the benefits of AI reach everyone across India through experiences and interactions that feel both natural and intuitive.
“This support fuels our continued investments in language and culture research, and drives us to make our foundational models, on which India is building its AI ambition, more effective and efficient in processing Indian languages,” he added.
Edited by Kanishk Singh
