AI Crop Nutrition App DevelopmentSearching

We are building an AI-powered mobile application designed to provide crop-specific nutrition and fertilizer recommendations. The app will utilize both rule-based logic and machine learning models to generate tailored nutrient dosages and fertilizer suggestions, leveraging agronomic data such as crop variety, soil characteristics, irrigation methods, plant population, and desired yield. Our aim is to create an effective decision support tool that bridges agronomy and technology for farmers and agri-input professionals, improving fertilizer efficiency and farm productivity. The project is currently in its early build phase, focused on data validation and system architecture, with plans for mobile and cloud backend support, and future integration of soil tests, satellite data, and regional databases. We seek a talented AI application development engineer experienced in Python/Node.js/TensorFlow/PyTorch and mobile/cloud backend systems to help shape the product’s intelligence and architecture. Prior experience in AgriTech, recommendation engines, or decision-support systems would be advantageous.

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About the client
I am an agri-business professional working on building an AI-powered crop nutrition recommendation application aimed at improving fertilizer efficiency and on-farm productivity. The product is designed to convert agronomic data—such as crop variety, soil type, irrigation method, plant population, and target yield—into practical, data-driven nutrient recommendations. The mission is to bridge the gap between agronomy and technology by delivering accurate, scalable, and easy-to-use decision support tools for farmers and agri-input professionals. We are currently in the early build phase, validating data and system architecture, and are looking to collaborate with a skilled AI application development engineer to help shape the core intelligence and platform. This project has strong potential for commercial deployment across multiple crops and regions, especially in emerging agricultural markets.