bookmark flowAI An R package containing two methods to clean flow cytometry files from unwanted events: A) an automatic method that adopts algorithms for the detection of anomalies, B) an interactive method with a graphical user interface implemented into an R shiny application. The general approach behind the two methods consists of three key steps to check and remove suspected anomalies that derive from 1) abrupt changes in the flow rate, 2) instability of signal acquisition, 3) outliers in the lower limit and margin events in the upper limit of the dynamic range. For each file analyzed our software generates a summary of the quality assessment from the aforementioned steps. The software presented is an intuitive solution seeking to improve the results not only of manual but also and in particular of automatic analysis on flow cytometry data. We recommend the usage of flowAI as a first preprocessing step of the data right after they are obtained from the flow cytometry instrument so that all the downstream analyses, from compensation to detection or rare cells, will benefit from it.