For flow cytometry, we acquired data digitally from cells on an improved digital system with faster ADCs and a faster FPGA, and used it to generate complex numbers we called “pseudophasors” from information about phase and amplitude. Plots of pseudophasors in the complex plane facilitated identification and “gating” of desired cell populations. We developed algorithms that computed pseudophasors on this digital hardware very rapidly, fast enough to permit their use to sort on small differences in Remdesivir lifetimes for hundreds of cells per second. We then used these capabilities to measure fluorescence lifetimes of isospectral live cell subpopulations, and to sort mixed populations into nearly pure populations we scored phenotypically by colorimetric assay of colonies descended from the sorted cells. The work opens the way to acquire fluorescence lifetime information from genetically encoded, fluorescent protein reporters in live cells at the high throughput provided by flow cytometry, and to sort and recover subpopulations of live cells with different lifetimes for further genetic and molecular analysis. We then used the modified flow cytometer to sort subpopulations by fluorescence lifetime. To do so, we used the same two waveforms, corresponding to excitatory and emitted light to generate pseudophasors for each passing cell. A plot of pseudophasors in the complex plane displays differences in lifetimes as differences in phase. Such a plot enables the investigator to easily select well-separated high-amplitude events for which the phase delay distributions do not overlap. We used these pseudophasor plots to draw polygons in the complex plane that defined sort gates. Over the past ten years, a substantial body of work has demonstrated the utility of flow cytometric measurements of cell signaling. These permit quantification of signaling proteins from fixed cells probed with fluorescent antibodies. Such studies have allowed identification of cell subpopulations that signal differently. Considerable attention to new methods of analysis has allowed researchers to use such data to make valid inferences about cause and effect relationships among measured variables, to canvass key changes in signaling caused by treatment with inhibitors of specific signaling proteins and to infer order of events and developmental trajectories for different cell types from collections of static measurements or snapshots. Here, we demonstrated the ability of flow cytometry to determine fluorescence lifetimes of XFPs in live cells, and to isolate cell subpopulations by sorting on lifetime. We imagine a number of ways that this new capability might positively impact future studies of cell signaling. The first is due to the fact that light signals from XFPs are weak.