Research and Development
At GreentecAI, research and innovation are the foundations of our mission.
Through advanced projects, academic partnerships, and collaboration with global research bodies, we are helping shape the next generation of AI technologies — built on trust, performance, and ethics.
Why Our Research Matters
The AI systems of tomorrow require visionary thinking and rigorous development today.
Through our active research initiatives, we are:
Advancing state-of-the-art AI algorithms to address real-world complexity.
Building ethical and transparent AI frameworks to ensure responsible innovation.
Developing scalable and adaptable AI architectures to drive cross-industry transformation.
Actively contributing to national and European AI research and policy initiatives.
Our research is not just about pushing boundaries — it's about creating AI that the world can trust.
Research Projects
🌱 Applied Research in AgriTech
At GreentecAI, we are conducting applied research in collaboration with University College London (UCL) to develop AI-driven tools that bring actionable intelligence to agriculture.
Our research currently focuses on two core projects:
1. Rice Yield Prediction
In partnership with UCL researchers, we designed a season-specific machine learning framework for predicting rice yields across ecotypes (Boro, T.Aus, T.Aman).
The framework integrates NASA POWER climate data with district-level agronomic management practices. It provides interpretable and uncertainty-aware forecasts, which we have already deployed in a prototype decision-support tool for agronomists and policymakers.
🔗 Download Rice Yield Preprint (PDF)
🔗 Access Prototype Tool
2. Soil Nutrient Prediction
We are building machine learning models that estimate soil nutrient availability (Nitrogen, Phosphorus, Potassium, organic matter, and key soil health indicators).
By combining remote sensing data, field surveys, and environmental variables, our models guide farmers and policymakers in optimizing fertilizer use reducing costs, improving yields, and minimizing environmental impact.
🔗 Download Soil Nutrient Paper
🔗 Download Dataset / Supplementary Material
Impact
Together, these projects tackle two fundamental challenges in agriculture:
Soil fertility management that is sustainable, cost-efficient, and climate-smart.
Yield forecasting under uncertainty to safeguard food security in smallholder-dominated systems.
By combining cutting-edge AI with field-ready applications, GreentecAI is shaping the future of climate-resilient agriculture.
Partnering for a Smarter Tomorrow
We are proud to collaborate with leading academic institutions, government bodies, and research organizations across the UK and Europe.
Our work contributes to a global movement towards AI systems that are innovative, ethical, and transformative.
Together, we are building a future where AI empowers industries, protects society, and inspires new possibilities.
