We focus on developing advanced computational techniques to rapidly and accurately identify fungi, microbes, and their functions from environmental and clinical samples, aiming to gain deeper insights into their biological processes. Our approach incorporates Artificial Intelligence (AI), clustering, visualization, and analytical tools and pipelines tailored for various data sources, including DNA barcodes, omics data, and images from fungal strains preserved in the Westerdijk Institute’s collections, as well as data from public repositories. Furthermore, we integrate diverse metadata associated with our fungal strains and species—such as morphological, pathogenic, geographic, ecological, and environmental data—to build a comprehensive understanding of fungal biodiversity, enabling us to efficiently and scalably uncover new insights into fungal biology, ecology, and their applications in medicine, agriculture, and industry.