Developed the foundational chat Q&A system for the rag2daw2025 and rag2daw2025frontend repositories, establishing a robust data model and service layer to support conversational AI features. Leveraged Java, Spring Boot, and Angular to implement advanced data filtering, dynamic queries, pagination, and real-time communication using Server-Sent Events. The work included restructuring the frontend for maintainability, building chat list and detail views, and enabling live chat updates with feedback mechanisms. This approach improved scalability and user experience by supporting incremental message delivery and advanced filtering, while laying the groundwork for comprehensive chat management and extensible, maintainable code across both backend and frontend.