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LegAI Diagnostics is an AI-powered medical tool designed to assist orthopedic specialists by analyzing X-ray images of leg bones. The system automatically detects fractures, misalignments, and other bone-related issues, providing quick, accurate insights to support diagnosis and treatment planning. This project demonstrates the integration of AI in healthcare, specifically focusing on enhancing leg bone diagnostics.

Designed and developed a web application that utilizes Hugging Face’s Large Language Models (LLMs) to automate the creation of engaging comic content from text inputs, streamlining the storytelling process. This innovative platform transforms ideas into visually compelling comic narratives with minimal effort, featuring AI-generated storytelling that converts text prompts into structured comic scripts with dialogues and narratives, character and scene generation that automatically creates diverse characters and dynamic settings based on input descriptions, customizable themes and styles to support various art styles and storytelling genres, and interactive editing that enables users to refine AI-generated content for greater creative control.

 

 

Developed and deployed an advanced AI-powered chatbot that simulates real-world cold-calling scenarios, providing an interactive training experience for sales representatives. Leveraging OpenAI’s models, the bot delivers dynamic conversations, evaluates responses in real-time, and offers AI-driven feedback to enhance sales techniques. It features realistic call simulations that mimic various customer personalities and objections, AI-powered feedback that analyzes tone, word choice, and response effectiveness, customizable scenarios that allow businesses to tailor training sessions based on industry-specific sales scripts, and performance tracking that generates detailed reports to measure progress and identify areas for improvement.

The app is a face recognition-based attendance system, designed to streamline attendance tracking. It captures and verifies faces in real-time, marking attendance automatically upon successful recognition. The app aims to reduce manual attendance efforts, improve accuracy, and provide instant reporting. It’s suitable for schools, workplaces, and events, ensuring secure and efficient attendance management.

Developed and optimized an AI assistant for the agricultural sector, leveraging Groq Cloud and LLaMA 3.1 to provide expert insights on crop management, soil health, and precision farming. Fine-tuned using diverse agricultural datasets, the model ensures accurate and context-aware recommendations for farmers and agronomists. It features intelligent crop advisory that offers data-driven guidance on planting, irrigation, and fertilization strategies, soil health analysis to assess conditions and suggest improvements for better yield and sustainability, precision farming insights that utilize AI-powered analytics to enhance productivity and reduce resource waste, and multilingual, context-aware support to deliver region-specific agricultural knowledge, making it accessible to farmers worldwide.