A multilingual AI-driven platform that allows users to ask agriculture-related questions in text or audio (Bangla/English). It retrieves relevant information from a vector database and generates detailed responses using a Large Language Model (LLM), providing answers in both text and speech formats.
Developed a scalable machine learning backend framework for efficient data processing, model deployment, and API services, enabling seamless integration of ML models into production environments.
An AI-powered tool that processes and analyzes uploaded research papers in PDF format. Using a custom-built Large Language Model (LLM), the bot extracts key insights, providing quick summaries and answers to specific questions, saving time and enhancing research efficiency in our agriculture startup.
Developed a computer vision-based system combined with regression models to accurately estimate water height in rice fields. This solution automates the measurement process, improving irrigation management by providing real-time, precise water level data for better resource allocation and crop management.