Mohamed Fazil@Fazil_24

Our project DocuMed involves developing an Gen AI-powered chat application using Streamlit and Falcon LLM to streamline patient data management for clinicians. The solution consolidates and summarizes each patient’s medical history, including EHR, lab tests, and imaging results, into a comprehensive knowledge base. This facilitates personalized care by reducing manual data entry, enhancing efficiency, and improving decision-making. Future plans include integrating this system into a decentralized platform for seamless data transfer across healthcare facilities. This tool is a radical approach to solve the problems of clinicians serving as their copilot

This project focuses on providing farmers in underserved communities with an intelligent AI-powered chatbot that addresses both general and complex queries related to plant care and farming. The system uses a Strategic agent approach: A local model (LLaMA 3.2 3B) running on an edge device to answer general, everyday plant care questions. A larger, cloud-hosted model (LLaMA 3.1 70 B) accessible via API for handling more complex or specialized queries. An intelligent agent is designed to assess the complexity of each query and assign a score. Based on the score, the agent dynamically routes the query to the appropriate model, optimizing for response time, computational resources, and accuracy. Farmers will interact with the system through a simple web or mobile chat interface (powered by Streamlit), enabling them to ask questions about plant health, harvest cycles, and more.