AgroAI - An Agricultural Technology Company
Client
AgroAI (An Agricultural Technology Company)Category
Backend Development, AI/ML Development, DevOpsDate
2020 - 2023Challenge
AgroAI needed comprehensive applications to support their vertical farming systems. The solution required the use of AI and machine learning to optimise crop yield, detect diseases, and manage water and nutrient levels while ensuring scalability and automation.
Process
Our team analysed their technology requirements and strategic goals, focusing on enhancing agricultural productivity and sustainability. We utilised Rust, TypeScript, React, AWS, Python, Node.js, and various AI/ML algorithms to develop and deploy the necessary applications.
We created high-performance Rust applications to handle large-scale image data processing, leveraging AI techniques for improved image analysis. Advanced machine learning models were implemented for predicting crop yields, detecting diseases, and managing water and nutrient levels.
To streamline development, we established a continuous integration and deployment (CI/CD) pipeline using Jenkins, GitHub Actions, and Kubeflow. This ensured rapid and reliable software updates, with automated AI model training and deployment.
Solution
We successfully developed and deployed end-to-end applications that integrated AI and machine learning for optimised crop yield predictions, disease detection, and water/nutrient management. The CI/CD pipeline facilitated fast and dependable software releases, with automated updates for AI models.
Results
The new system significantly enhanced AgroAI's vertical farming operations, improving productivity and sustainability. The applications provided accurate crop yield predictions, early disease detection, and efficient water/nutrient management. The streamlined CI/CD pipeline ensured rapid, reliable updates and reduced technical debt, resulting in higher software quality and reliability.