We present Marcel, a lightweight and open-source conversational agent designed to support prospective students with admission-related inquiries. The system aims to provide fast and personalized responses, while reducing workload of university staff. We employ retrieval-augmented generation to ground answers in university resources and to provide users with verifiable, contextually relevant information. We introduce a Frequently Asked Question (FAQ) retriever that maps user questions to knowledge-base entries, which allows administrators to steer retrieval, and improves over standard dense/hybrid retrieval strategies. The system is engineered for easy deployment in resource-constrained academic settings. We detail the system architecture, provide a technical evaluation of its components, and report insights from a real-world deployment.
@article{arxiv.2507.13937,
title = {Marcel: A Lightweight and Open-Source Conversational Agent for University Student Support},
author = {Jan Trienes and Anastasiia Derzhanskaia and Roland Schwarzkopf and Markus Mühling and Jörg Schlötterer and Christin Seifert},
journal= {arXiv preprint arXiv:2507.13937},
year = {2025}
}