Our community, focused on increasing transparency in international aid, proposes the innovative use of RAG to analyze and interpret IATI data. We aim to train an LLM with this data, augmented through RAG, to provide deeper insights into aid allocation, effectiveness, and outcomes. The project will involve processing extensive IATI datasets using RAG to create structured, informative graphs that an LLM can learn from. This application of AI could significantly enhance the understanding and transparency of international aid, potentially influencing policy decisions and aid effectiveness on a global scale. Such a methodology could also serve as a blueprint for other sectors seeking to leverage complex data for enhanced decision-making and transparency.