Giselle: A RAG-Based Generative AI Platform for Mental Health Care

The launch of GPT-3 by OpenAI in 2020 revolutionized the field of Natural Language Processing (NLP) by introducing highly advanced generative AI models capable of performing complex tasks. This breakthrough accelerated the global adoption of artificial intelligence in various fields, including automation, customer support, and content creation.However, in the healthcare sector, the use of generative models requires caution, as errors or "hallucinations"can have serious consequences. A promising approach to improving the safety and accuracy of these tools is Retrieval-Augmented Generation (RAG), which enables the model to access external information in real time, ensuring up-to-date content, solution customization, and greater transparency—without the need for retraining—while significantly reducing the risk of hallucinations.In this context, this study explores the application of RAG in the Giselle Saúde project, an initiative funded by Embrapii/MCTI, which leverages generative AI to detect signs of depression in the elderly.