GreenLeaf Automation
An AI-powered crop monitoring and automated reporting system that replaced manual field inspections with intelligent satellite-image analysis.

Challenge & Context
GreenLeaf's agronomists spent 60% of their time on manual field inspections and report generation. The data they collected was inconsistent and often outdated by the time reports reached decision-makers.
Engineering Execution
We built a system that ingests satellite imagery and weather data, runs analysis through trained ML models, and generates actionable field reports automatically. Human expertise guides the system rather than duplicating its work.
DESIGN & ENGINEERING EXECUTION
The interface uses a map-first design with overlaid data layers. Reports are generated as structured documents with clear severity indicators and recommended actions.
Python ML pipeline with TensorFlow for image classification, FastAPI backend, React dashboard, PostgreSQL for structured data, and S3 for satellite imagery storage.
MEASURABLE OUTCOME
TECHNOLOGIES LEVERAGED:
VISUAL ARTIFACTS


This system was architected under our Capabilities & Services matrix. Exploring custom web development in Northeast India? View our Guwahati Web Design Studio or explore Rajat Pradhan’s Full Engineering Portfolio.