Using AI techniques such as Retrieval-Augmented Generation, vector search, and graph-based exploration, SARA helps users quickly find relevant content, extract insights, and trace connections across themes and timelines. Rather than relying on manual search and review, it enables more efficient engagement with large bodies of text, turning static archives into dynamic knowledge sources.

Originally developed as an internal research tool, SARA is designed to be adaptable across different organisational contexts. Its architecture makes it suitable for use in governmental organisations, research institutes, or private sector environments where large document collections play a central role—offering a structured approach to analysing accumulated knowledge and informing ongoing work.