Bioimage workflows have transformed quite dramatically over the last year, making once thought impossible challenges like 3D segmentation of complex data possible. Meanwhile, new imaging modalities are breaking records in both resolution and acquisition speed, generating gigabytes if not terabytes of data. This transition is powered by a new generation of tools like Napari (for visualising big datasets), and deep learning-based methods such as CARE or Stardist, which are co-existing with proven apps like ImageJ or MicroManager. However, with this shift in bioimage workflows comes the burden of orchestration and data management, that is hindered not only by the variety of software platforms these tools are developed in but also by the requirement for dedicated computing resources (GPUs, High-Performance Computing). This causes existing methods to be still limited in their interoperability. In this workshop, we will explain the challenges of modern bioimage workflows, especially real-time data analysis and management. Furthermore, we will introduce our solution to this problem: Arkitekt - a powerful middleman between users and bioimage apps for building and orchestrating real-time analysis and microscopy workflows. The workshop will rely on conventional bioimage software (ImageJ, Napari, Micro-Manager) and modern deep learning frameworks (CARE, StarDist) to build advanced data pipelines that can go from acquisition to statistics. It will also demonstrate Arkitekt’s capability to set up a “Smart Microscopy” workflow by modifying microscope acquisition parameters in real time according to on-the-fly detection of specific events.