Quantitative microscopy workflows have evolved dramatically over the last years, progressively becoming more complex with the emergence of deep learning. Long-standing challenges like 3D segmentation of dense microscopy data can finally be addressed, and new imaging modalities are breaking records in both resolution and acquisition speed, generating gigabytes if not terabytes of data per day. This evolution necessitates advanced orchestration and data management solutions that reckon with the reality of modern multi-tool environments and the increasing need for dedicated computational resources like GPU and CPU clusters. However, existing solutions often lack dedication to bioimage analysis and accessibility for non-experts and are predominantly designed for batch-style analysis. This limits their applicability to dynamic "smart microscopy" workflows that require real-time analytical feedback to inform ongoing experiments. Here, we present Arkitekt, an open-source middleman between users and bioimage apps that enables the orchestration of complex quantitative microscopy workflows in real time. It interfaces with popular bioimage software, like FIJI and Napari, both locally and remotely, while managing their data FAIRly on a central server. It includes visualization and analysis modules, but also mechanisms to execute source code and pilot acquisition software, making “smart microscopy” a reality.