growclusters is an R package that estimates a clustering or partition structure for multivariate data. Estimation is performed under a penalized optimization derived from Bayesian non-parametric formulations. This is done either under a Dirichlet process (DP) mixing measure or a hierarchical DP (HDP) mixing measure in the limit of the global variance (to zero). The latter set-up allows for a collection of dependent, local partitions. This paper revisits the two R Shiny applications that were introduced in our 2019 paper and will focus on additional functionality added to both of them, as well as the integration of the R Shiny applications into the growclusters package. We will also present an example where the R Shiny applications are used to analyze the text from past papers presented at the United Nations Economic Commission for Europe workshops.