EurecaChat: A Multi-Agent LLM-Based Chatbot for Supporting Students, Faculty, and University Administration - Figueiredo e Silva, Matheus Hensley de; Pereira Júnior, Levi de Lima; Pereira, David Eduardo; Meneses, Beatriz de Souza; Lima, Kemilli Nicole dos Santos; Araujo Junior, José Robson da Silva; Marinho, Leandro Balby; Araújo, Eliane Cristina (Anais Estendidos do Simpósio Brasileiro de Sistemas Multimídia e Web (WebMedia), 2025)
Academic data plays a crucial role in guiding students as they plan their curricular paths, supporting professors in refining their courses, and enabling administrators to make evidence-based decisions. Despite its importance, such data are often difficult to access. Even under open data policies, barriers to usability and accessibility frequently limit its impact. In this work, we present EurecaChat, a multi-agent chatbot system that allows users to retrieve academic data through natural language. Built on Large Language Models (LLMs), EurecaChat tailors responses to the needs of different user profiles: students, faculty, and staff, while ensuring compliance with data privacy constraints. Preliminary evaluation shows good performance in several use cases, underscoring the potential of the system to democratize access to academic data and promote more informed decision making in educational environments.