We present dyngen, a multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. dyngen is more flexible than current single-cell simulation engines, and allows better method development and benchmarking, thereby stimulating development and testing of computational methods. We demonstrate its potential for spearheading computational methods on three applications: aligning cell developmental trajectories, cell-specific regulatory network inference and estimation of RNA velocity. To benchmark single cell bioinformatics tools, data simulators can provide a robust ground truth. Here the authors present dyngen, a multi-modal simulator, and apply it to aligning cell developmental trajectories, cell-specific regulatory network inference and estimation of RNA velocity.