Making agricultural information actionable.
A farmer-focused decision-support platform combining agricultural advisories, weather intelligence, machine learning and multilingual conversational assistance.
Prototype ready · Field validated · Vellore pilot
AgriLens is a student-led agricultural decision support initiative focused on helping farmers make more informed crop planning and risk management decisions. Our incubations was funded by GIZ, under the India Food Systems Tranformation Hackathon 2026, with its summit in Bengaluru on March 6-7th, 2026 and Delhi on 7th October, 2026.
Our goal is to combine climate data, soil information, market trends, and local agricultural advisories into a simple, accessible platform that supports farmers throughout the crop cycle. Rather than relying on a single recommendation, AgriLens aims to provide timely insights on crop suitability, weather-related risks, market conditions, and field-level advisories in a format that is easy to understand and use.
The project is currently being iteratively developed and tested through farmer interviews, public agricultural datasets, machine learning models, and collaboration with agricultural stakeholders. Our first pilot focused on the Vellore–Tirupathur region of Tamil Nadu, with an emphasis on building practical tools that are grounded in real farmer needs and field feedback.
We believe that technology is most useful when it complements local knowledge. AgriLens is therefore being developed through continuous interaction with farmers, researchers, and agricultural extension networks to ensure that recommendations remain relevant, transparent, and actionable.
What we've built:
An LLM-based pipeline that processes agricultural advisory bulletins, extracts relevant crop and livestock recommendations, and converts complex technical information into structured, farmer-oriented guidance.
Vellore District, Tamil Nadu.
Pilot 1 : August 7th-8th, 2026
A conversational interface, nicknamed Vaani(Vernacular AI for Agrometeorology and Nowcasting in India). allowing farmers to interact with AgriLens through voice, ask questions and receive agricultural information in an accessible format.
A machine-learning component designed to analyse agricultural, environmental and market information to support crop-level decision making - currently in the prototype phase.
Development of cloud-based architecture and data pipelines for a low-cost mobile app.
India Food Systems Transformation Hackathon 2026
Mentor: Prof. C Shambu Prasad, IRMA
Contact team@agrilens.org to get more information about the project