Growing the Future
from Above

Meet our strategy

CropAuditing is a technological framework designed to enhance the monitoring of large-scale agricultural areas through the integration of satellite imagery (Sentinel-2) and Machine Learning algorithms. Our solution addresses the limitations of traditional manual surveys by providing an automated, scalable, and precise system for crop species identification and growth stage tracking. By converting complex geospatial data into verifiable analytical reports, the platform optimizes the auditing process for financial institutions and insurance companies. We aim to ensure data transparency, facilitate fraud detection, and provide stakeholders with the necessary tools for informed decision-making in the evolving agricultural landscape.

Crop Identification

Using Machine Learning and statistical analysis to accurately identify crop species and calculate their specific land areas.

Growth Monitoring

Leveraging Sentinel-2 satellite imagery to automatically determine and track the growth stages of plantations.

Automated Auditing

Replacing slow manual surveys with a fast and user-friendly digital process for insurance companies and financial institutions.

Fraud Detection

Ensuring data transparency to facilitate fraud prevention and simplify compliance with agricultural government aid programs.