Most of the Web is published in languages not accessible to many potential users who can read and understand only their local languages. Previous Information Retrieval (IR) approaches, particularly those used in Cross-Lingual Information Retrieval (CLIR) and Multilingual Information Retrieval (MLIR), have focused on the translation of either queries or documents in the retrieval pipeline. Unfortunately, many of the local languages lack the necessary resources, such as machine translation, to make the available content accessible. In this talk, I will discuss my work on using intelligibility in retrieval, focusing on South-Eastern Bantu languages. I will show that by matching search results written in related languages, incorporating intelligibility in the ranking, and presenting the results appropriately, we can improve retrieval effectiveness and user experience for speakers of resource-scarce languages.