With modern discovery layers, libraries are finally able to integrate all of their content into a single search experience, but fluid discovery across content sources using a single interface is still lacking. Users are typically given one of two options: 1) bento box results where once a user chooses a path they must start their search over to switch content sources 2) federated searches that mash everything together in a muddled mess, hiding the most relevant resources. Using linked data and smart algorithms, we will demonstrate how Marmot is enhancing the open-source Pika discovery layer to create an experience that combines the best of these scenarios. Users looking for books will have the opportunity to discover related digital content at every step as their search evolves. Users researching digitized historic photos will be offered books on the history of the places they’re looking at. This type of fully integrated discovery layer allows users to focus on their primary research objective while revealing previously hidden gems.