Sowing Seeds of Agri AI models, from India to APAC
Throughout our AI journey in India, Google has strongly believed that solutions that address India’s most pressing challenges can also solve for the world. Today, we’re extremely proud to announce a measurable step forward that speaks to this conviction.
We are expanding our freely available agricultural model outputs as APIs - Agricultural Landscape Understanding (ALU) API and Agricultural Monitoring & Event Detection (AMED) API - which were first built to strengthen India’s agricultural resilience, to now also support agricultural sustainability across the Asia-Pacific region. We are thrilled to start opening access to these APIs to trusted testers in Malaysia, Vietnam, Indonesia, and Japan, within just months of these models’ India-first releases.
The ALU and AMED foundational models leverage remote sensing and machine learning to provide the local ecosystem with insights that can help build cost-effective, simple and targeted agricultural solutions. The ALU API will identify fields, water bodies, and vegetation boundaries, while AMED API will deliver critical field-level insights on the most cultivated crops, and their sowing and harvest timelines at individual field levels. AMED API will also refresh data actively, approximately every 15 days, helping detect agricultural events in individual fields throughout a country’s agricultural landscape.
Together, these models provide essential information and insights that serve as a base layer for the agriculture ecosystem to develop precision agriculture tools, optimize resource allocation, and improve farm management practices. Take a look at how these models have been deployed in India so far:
The Indian ecosystem continues to unlock a variety of use cases for these models towards strengthening the resilience of the local agri sector - from policy planning, to crop advisory, and even financial access.
- Krishi DSS, an integrated agri-insight and decision-making platform being developed by Amnex for the Government of India’s Department of Agriculture and Farmer Welfare, is leveraging the ALU and AMED APIs to power advanced analytics for crop health monitoring, acreage estimation, irrigation advisories, and climate impact assessment. These capabilities will empower policymakers and field officers to make timely, informed decisions across districts, tehsils, and villages.
- Vassar Labs plans to integrate the APIs into its existing fieldWISE platform and data stacks, offering a comprehensive climate-smart agriculture platform. Serving over 1 crore Indian farmers through several state projects, the integrations will enhance its existing solutions for different terrains and cropping patterns - from crop and field monitoring for agriculture departments, to personalized advisories on crop, irrigation, pest, and fertilizer management, as well as market and pricing dynamics for farmers.
- Sugee.io, which aims to democratize financial access for rural communities, is integrating insights from ALU API directly into its loan origination system towards improving efficiencies in the application process for the farmers, while also supporting the quality, reliability and compliance of agricultural loans for banks. Sugee also plans to use AMED API to advise credit monitoring and risk management, helping banks evaluate farm loan applications and monitor for event-based variations and repayment risks throughout the loan tenure.
- Council on Energy, Environment and Water (CEEW) plans to use the ALU and AMED APIs to develop first-of-its-kind, high-resolution analysis that will help identify regions that can benefit most from crop diversification. This foundational insight will enable CEEW to conceptualize a new mechanism for direct, responsive and differentiated income support to farmers, nudging them to grow more nutritious and climate-friendly crops. CEEW is also integrating the models into its Climate Data Platform, which will be available as a digital public good for guiding targeted state-level interventions.
The use cases in India demonstrate our AI models are essential starting points for massive change, paving the way for solutions that are accurate, scalable, and assist targeted, data-driven action.
The expansion of these Agri-focused AI models marks a pivotal opportunity for APAC agriculture. We invite developers, researchers, and agri-businesses across the region to partner with us and leverage these models to pioneer new, scalable solutions that accelerate regional food resilience, uplift farmer livelihoods, and set a new global benchmark for sustainable agriculture.
