In law enforcement and security, investigators spend considerable time and resources manually sifting through large amounts of ”indicative” information to identify persons of interest. It is time for research to find effective solutions to accelerate this process. For example, blocking the browser’s hours can significantly slow down the browser’s progress. This research focuses on developing a chatbot designed to help researchers analyze video recordings to identify individuals based on a reference database. The main goal is to reduce the time and effort involved in manually reviewing extensive video footage. By integrating a chatbot with advanced facial recognition software, the system can effectively manage video content and accurately identify people of interest. A chatbot can speed up the research process and provide accurate and precise results. This innovation will be able to increase the efficiency of research, reduce the costs of operations, and improve the accuracy of video surveillance. Future research will focus on optimizing the system’s performance and expanding its capabilities to handle larger datasets and more complex search tasks.