The field of developmental biology is undergoing a profound transformation, driven by groundbreaking advances across multiple disciplines. Light-sheet microscopy enables rapid, large-scale, multicolor imaging of developing embryos in unprecedented detail, allowing scientists to capture dynamic processes as they unfold in real time1,2,3. Simultaneously, the advent of advanced cell tracking technologies, such as Ultrack4, Linajea5, Elephant, TGMM6, Trackmate, Mastodon and TrackAstra, has made it possible to follow individual cells throughout embryonic development with remarkable precision and speed. These innovations, which have emerged in the past two decades, are only now realizing their full potential for embryology. This unprecedented level of detail opens the door to answering fundamental questions about tissue development, organ formation and the intricate orchestration of the cell behaviors that govern the entire embryo7.
While these imaging datasets hold the potential for biological insights, accessing and interacting with such complex data typically demands highly specialized technical expertise and substantial computational resources. Existing software tools allow visualization and analysis of cell tracking data (for example, napari8, TrackMate’s TrackScheme, Mastodon and CellTracksColab), However, while powerful in their respective application domains, most of these approaches require native software, have limited 3D support, or are intended for the curation of tracks, not the interactive exploration of large cell tracking datasets. Consequently, only a limited subset of researchers can fully leverage these data, creating a barrier to broader adoption.