The increase of textual data volumes necessitates a swift progression in data science, particularly in Natural Language Processing (NLP). The UniDive action is centered on the task of preserving linguistic diversity, with a focus on understanding both the differences between languages and the nuances within them. UniDive reframes technology from a potential threat to an ally in embracing linguistic diversity. The strategy of UniDive includes developing universal NLP methodologies, evaluating linguistic diversity, and refining various linguistic tools, prioritizing support for less represented languages.