Bengaluru based agritech startup, Fyllo, has launched DeepMet 1, an AI enabled hyperlocal weather prediction model developed to provide real time rainfall intelligence with a six hour forecasting window. The model has been created to support users who depend on timely, localized weather updates, spanning farmers, urban planners, energy operators, logistics providers, researchers, and fintech platforms.
Designed for India’s Diverse Climatic Zones
DeepMet 1 has been built specifically for the Indian subcontinent, where unpredictable rainfall patterns frequently disrupt on ground operations. Traditional weather systems often provide broad regional estimates that fail to capture local variations, leaving weather dependent sectors vulnerable to delays, operational challenges, and financial losses. DeepMet 1 addresses this gap by offering hyperlocal rainfall predictions at a 10 × 10 kilometre resolution, allowing stakeholders to base their decisions on conditions relevant to their immediate surroundings.
The system is positioned to support critical sectors that require precise updates on short term rainfall, including agriculture, urban infrastructure, power distribution, warehousing, supply chain management, transportation networks, and digital financial services. Accurate rainfall insights directly influence actions such as irrigation scheduling, harvesting, crop protection, road mobility, energy load management, and delivery planning.
DeepMet 1 Generates Hyperlocal Intelligence
DeepMet 1 processes satellite observations from the preceding six hours to forecast precipitation levels for the next six. This continuous assessment enables the model to interpret micro level weather behaviour, detecting variations between neighbouring villages, streets, or even patches of farmland. These granular updates allow users to anticipate rainfall with sharper accuracy, reducing uncertainty in day to day operations.
The model is designed for real time, high frequency deployment. It integrates seamlessly into existing systems through API access, making it suitable for organizations that require automated weather inputs as part of their operational workflows. Developers, research institutions, and enterprise teams can also use the model’s live dashboard to visualize ongoing rainfall forecasts, enabling broader application development and strategic weather dependent planning.
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Online delivery platforms stand to benefit as well by utilizing DeepMet 1 to predict delivery duration, route efficiency, and cost implications during periods of rainfall. This can help reduce delays, lower operational expenditure, and improve customer experience.
Sumit Sheoran, Co-founder of Fyllo, emphasized that India’s weather ecosystem demands more dynamic and location-specific tools. He noted that farmers, city planners, and energy managers frequently depend on general forecasts that do not reflect local ground realities.
India’s diverse weather necessitates dynamic tools for accurate forecasting. Farmers, city planners, and energy managers often rely on general forecasts that overlook local conditions and specific needs. DeepMet 1 aims to address this by providing hyperlocal, AI-driven weather intelligence, making it accessible to all stakeholders.
DeepMet 1 within Fyllo’s Broader Technology Ecosystem
The launch of DeepMet 1 aligns with Fyllo’s long term mission to make farming more predictable through data driven decision making. The startup has expanded across major agricultural regions of India, offering solutions that provide farmers with real time insights on crop health, nutrient requirements, irrigation needs, and potential disease outbreaks. Its digital ecosystem is used by thousands of farmers and agri enterprises and is supported by investors including India Quotient and SIDBI Venture Capital.
With DeepMet 1, Fyllo adds a climate intelligence layer to its growing suite of tools. The model strengthens the company’s commitment to delivering hyperlocal, accessible, and actionable insights, enabling agriculture and multiple adjacent industries to better navigate India’s unpredictable weather patterns. As weather variability continues to influence productivity and operational efficiency across sectors, DeepMet 1 stands as an important advancement in providing reliable short term rainfall intelligence to users who require timely, accurate data to sustain performance and improve planning.
