This chapter explores the landscape of Artificial Intelligence (AI) tools and technologies specifically suited for academic research, emphasizing the role of locally run Generative AI (GenAI) applications. By examining the structure of data management technologies and AI software components, the chapter illustrates how researchers can leverage data-driven AI systems to build knowledge bases from scientific data. It highlights the value of Retrieval-Augmented Generation (RAG) systems for processing and referencing local documents, underscoring their relevance to the knowledge-intensive nature of research. Additionally, the chapter discusses open-source software (OSS) for ensuring transparency and repeatability, and reviews essential hardware configurations needed for efficient local AI deployment. This work aims to equip researchers with the understanding required to select AI tools that enhance their research workflows, offering insights into both foundational principles and practical applications of AI in academic settings.