Prism RCL: AI-Powered Medical Research Assistant

Developed a cutting-edge Proof of Concept for an AI-powered medical research assistant, integrating Random Contrast Learning (RCL) with GPT-4o-mini. This Python-based chatbot analyzes both medical text and images, achieving 99% accuracy in breast cancer detection from image data. Utilizing a RAG (Retrieval-Augmented Generation) pipeline, the system offers an intuitive natural language interface for medical professionals. The project demonstrates the powerful combination of RCL and advanced language models in healthcare, showcasing potential for improved medical analysis and diagnosis, particularly in oncology.

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Competitor Analysis AI System

Developed an AI-driven competitor analysis tool using multi-agent architecture, advanced data processing, and large language models. The system integrates diverse data sources, employs Retrieval Augmented Generation and knowledge graphs for insights, and features an interactive user interface. It provides real-time, accurate competitor information, significantly enhancing strategic decision-making capabilities for businesses.

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Enercalc AI Enhancement: Proof of Concept for AI-Driven Structural Engineering Assistant

Developed a Proof of Concept for enhancing Enercalc structural engineering software with advanced AI capabilities, creating a JARVIS-like assistant for engineers. This POC integrates machine learning, large language models, and cloud technologies to revolutionize structural analysis and design processes. Key features include AI-powered structural optimization, a natural language interface for intuitive interactions, predictive maintenance suggestions, and sustainability integration. Leveraging AWS services and MongoDB Atlas, the system demonstrates scalable cloud-based architecture for high-performance computing. This project showcases the potential to significantly enhance decision-making and efficiency in structural engineering workflows, positioning AI as a transformative force in the field.

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