Adaptive tutoring systems have demonstrated significant improvements in math learning, yet their adoption outside of the United States remains limited. The absence of these technologies, along with a lack of research on localizing tutoring systems to different educational contexts, presents a significant barrier for institutions seeking to integrate these tools into their classrooms to support students' math learning. This paper presents a case study on the localization and deployment of OATutor, an adaptive tutoring system developed in the U.S., for use in a math course at KTH Royal Institute of Technology in Sweden. Our study explores using artificial intelligence to automate and validate this process, focusing on translation and syllabus adaptation to ensure the content aligns with the course curriculum and the Swedish educational context. We successfully deployed the system in the course, demonstrating a novel method for translating math content and providing an analysis of syllabus adaptation tailored to the local context. By documenting this process, we contribute to the broader effort to make educational technologies more accessible to diverse learner populations by providing a scalable approach to localization.