Muhammad Hamza
AI Engineer | LLM AI Agents & RAG Automated Support Systems
Profile in progress
Muhammad is building their profile!
We've all been there: spending 30 minutes browsing Netflix, only to re-watch The Office for the 10th time.
I wanted to fix that "what should I watch?" problem. So, I built a custom neural network from scratch using TensorFlow/Keras. It analyzes massive datasets of user behavior and maps complex relationships between viewers and films.
The result? A highly accurate recommendation engine that serves up the perfect top 5 movies based on individual taste. It's like giving every user their own personal film buff.
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Your business needs a front desk that never sleeps!
I developed a custom RAG chat agent that takes the friction out of scheduling. From answering specific queries to booking the actual appointment and sending confirmation details, it handles the entire customer journey flawlessly. No more back-and-forth emails or phone tag. Just seamless, automated calendar management.
Ready to upgrade your booking process? Let's build your agent.
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Retrieval-Augmented Generation (RAG) Conversational Agent
Built using Python and FastAPI, the backend leverages RESTful APIs and asynchronous processing to ensure high-speed data handling and seamless system performance. The architecture is optimized for scalability, security, and maintainability, making it suitable for high-volume processing environments.
A dedicated test UI was developed to validate system functionality, improve usability, and ensure a smooth user experience. The interface is structured with staff convenience in mind, enabling intuitive navigation, simplified data access, and efficient task management — ultimately improving productivity and reducing operational complexity.
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RAG-Based AI Assistant for Automotive Customer Service
Developed an intelligent AI-powered chatbot for an automotive company to automate customer support and sales inquiries. The system handles car model details, pricing, availability, financing options, service bookings, and test drive scheduling. Integrated with a knowledge base using RAG to provide accurate, real-time responses from company data. Designed to improve customer engagement, reduce response time, and increase lead conversion through 24/7 automated support.
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