Ankon Ahamed

Contributed to the development of AGI, an Automated Rice Grain Detection system designed to support faster and more consistent grain analysis. Built and improved computer vision workflows for rice grain image processing, feature extraction, detection, and classification tasks. Dataset preparation, image annotation, preprocessing, and data quality improvement to strengthen model performance and reliability. Assisted in training, testing, and evaluating deep learning and machine learning models for grain detection and quality-related analysis. Supported backend integration and deployment workflows so the detection pipeline could be used in a practical application environment.

Built and improved AI-powered task orchestration workflows for intelligent planning, execution, and automation. Developed LLM-based agent pipelines for multi-step task handling, response generation, and workflow coordination. Contributed to backend API development, prompt workflow design, and integration of automation services with application modules. Supported debugging, deployment, and performance improvements for scalable AI-powered product features. Collaborated with the product and engineering team to ship production-ready automation capabilities.