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.