Juro: a retrieval-augmented generation AI chatbot for enhancing legal information access in resource-constrained settings

Abstract

Access to legal information remains a significant challenge in resource-constrained settings where the digitization of legal systems is still in its early stages. To address this issue, we developed Juro, an AI-based chatbot architecture utilizing a Retrieval-Augmented Generation (RAG) framework. Leveraging a curated dataset of over 8,400 legal documents, Juro provides a user-friendly platform that simplifies complex legal language and ensures information reliability through a robust source citation mechanism. This paper demonstrates the applicability of adaptable AI-driven solutions in low-resource environments, offering a flexible chatbot architecture that can be tailored to various contexts where information accessibility remains a critical challenge. The legal system in the Democratic Republic of Congo (DRC) serves as a use case, illustrating the potential of Juro in addressing similar challenges across developing countries.