The nanoaggregates synthesized under continuous flow were directly passed to an inline DLS for analysis via a flow cuvette, and a python script was written to control the flow and to control the entire nanoparticle synthesis and analysis platform, establishing the pathway for continuous screening of nanoaggregate sizes and real-time monitoring of particle sizes (see supporting information for details). Importantly, the platform was not only meant to perform pure operation of particle synthesis and analysis, but it was also built to perform the post-analysis functions automatically, which included digital handling of the large amount of data generated. These additional automated functionalities included direct data processing, data analysis, data cleaning, data aggregation and visualization, facilitating the user to get a quick insight into the trends realtime on screen, allowing enhanced accessibility to meaningful data sorted out without any human bias. An important part of this feature is automatic data cleaning. Even under machine operation, small fluctuations can occur (be it from flow instabilities or small impurities entering the system at time), which still makes the synthesis and analysis error prone. Since a large array of data is difficult to screen for a manual operator, the code conducted an automatic outlier detection, and reacted with follow up experiments automatically where required (see below).