QAssist is designed to help improve the quality assurance process for natural-language requirements by providing automated assistance in the form of instant answers to questions, thereby reducing the need for manual analysis and increasing efficiency. By using a combination of information retrieval and machine reading comprehension models, QAssist is able to extract the relevant context and answer from both the input document and external sources. The tool accepts a natural-language question and a software requirements specification document as input. With the help of information retrieval models, it identifies the input-document domain and extracts the relevant context for the given question using both the input document and a domain-specific corpus created from Wikipedia. The tool uses machine reading comprehension models to extract the exact answer from the identified contexts. The tool is publicly available on both GitHub and FigShare. QAssist is associated with the ICSE 2023 technical paper, titled “AI-based Question Answering Assistance for Analyzing Natural-language Requirements.”