In the age of advanced artificial intelligence, this thesis attempts to extend conversational question-answering (QA) agents' power by integrating them with session management and document retrieval functionality. The first goal is to give conversational agents the ability to get and extract information from a company's document repository which enables it with greater power to provide answers based on the organizational information. The research starts by doing a complete investigation of current conversational QA agents' situation and outlines their weaknesses with their ability to understand the context and information retrieval and exploiting and better utilization of the organization’s internal knowledge repository and the need for more efficient session management.