Artificial Intelligence (AI) is the pinnacle of digitization; it is a technology that will revolutionize the way we work and live. With AI, we can develop models capable of understanding natural language and answering questions based on different data sources. In this talk we will present the development of a conversational agent, in Python, capable of answering questions about the legacy of women scientists. We will show how we collect data from Wikipedia and create our training data. We will also present how to re-train Huggin Face Deep Learning models with our own data, in this case related to the legacy of women scientists. Our motivation for this development is born due to the low percentage of female scientists (28.5%, according to UNESCO). This conversational agent acts as a natural language user interface to disseminate historical facts that show that women can have a great contribution in areas such as science and technology, motivating young women to follow the example of great figures in the history of the humanity.