This project focuses on optimizing the user research tool Betafi by introducing new features that streamline the analysis and synthesis of data from user interviews. The aim is to improve researchers' workflows, helping them manage session-level insights, identify project-wide patterns, and communicate findings more effectively. At the session level, the tool enhances data organization by allowing researchers to tag, sort, and analyze feedback efficiently, enabling clearer insights. At the project level, it aggregates insights from multiple sessions, helping identify recurring patterns across data. With a more intuitive, visual interface, researchers can easily navigate large datasets and uncover connections between user inputs, speeding up the identification of key themes. The tool also improves communication by enabling researchers to share session-specific and project-level insights with stakeholders, fostering better collaboration. Overall, the project enhances the research process by improving data synthesis and communication, empowering teams to derive deeper insights, streamline decision-making, and effectively share findings.