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KishanSaathi

KishanSaathi is an AI-powered agritech platform that empowers farmers with predictive insights and financial access by leveraging satellite imagery, historical data, and Facebook’s Prophet model.

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Descripción

KishanSaathi is a full-stack agritech platform developed to revolutionize the way Indian farmers access predictive insights and financial services. By combining satellite-based geospatial intelligence, historical agricultural data, and advanced forecasting models like Facebook’s Prophet, KishanSaathi provides farmers with tailored recommendations and financial empowerment—all through a secure digital ecosystem.

At the core of the platform lies a Climate Score—a novel alternative to the traditional CIBIL Score. Recognizing that farmers often lack formal credit histories, the Climate Score evaluates agro-climatic performance metrics to assess creditworthiness. It factors in:

  • Crop health indices (e.g., NDVI, EVI from Landsat & Sentinel imagery)

  • Rainfall consistency and anomalies over cropping seasons

  • Yield stability across previous years

  • Local climate risk factors such as drought/flood zones

  • Soil moisture levels, temperature deviations, and pest risk assessments

This score enables banks, NBFCs, and microfinance institutions to make data-backed lending decisions, empowering climate-resilient financial inclusion.

The Prophet model by Facebook is used to forecast key agricultural indicators, including:

  • Future yield estimates based on seasonal patterns and climate regressors

  • Weather predictions tailored to specific geolocations

  • Market price trends for commodities to help farmers time their sales

  • Water requirement forecasts based on evapotranspiration and crop cycles

The system is powered by a secure backend with JWT-based authentication, ensuring user-level data privacy while enabling scalable interactions among farmers, agronomists, and financial entities.

In addition, KishanSaathi provides a suite of embedded financial tools, including:

  • Access to climate-linked microloans

  • Crop insurance eligibility based on forecasted risks

  • Tracking of government subsidies and payouts

By merging remote sensing, machine learning, and fintech innovation, KishanSaathi redefines agri-credit systems for the underserved, building climate-resilient rural economies and reducing dependency on outdated credit metrics.

Progreso del hackathon

Day 1: Ideation & Architecture Planning Completed problem statement: Climate intelligence based data-driven farming & credit scoring User personas defined: small/marginal farmers, financial institutions System architecture sketched out: Frontend (React) Backend (Node.js + Express, JWT-based Auth) Data Layer (PostgreSQL + Remote Sensing Datasets) ML Layer (Facebook Prophet) Day 2: Core Development Added Landsat & Sentinel API access for vegetation index and land cover data Preprocessed historical crop yield and climate dataset Implemented Prophet-based time-series forecasting for: Rainfall Yield prediction Market trends Day 3: Feature Implementation & Testing Built Climate Score engine to replace legacy CIBIL scores with: Vegetation health (NDVI) Rainfall anomalies Yield stability Secured backend with JWT-based authentication Deployed dashboard for: Forecast visualization Credit eligibility Crop advisory Day 4: Final Touches & Demo Preparation Integrated financial services module (microloans, insurance, subsidy tracking) Completed end-to-end testing of workflows (user registration → Climate Score → loan eligibility) Designed and practiced live demo & pitch

Pila tecnológica

React
Python
Express
Flusk
Jupyter
MongoDB
FireBase

Estado de recaudación de fondos

NA

Líder del equipoNniruponpal2003
Sector
AIOther