The increasing risk of epidemics and a fast-growing world population has contributed to a great investment in phylogenetic analysis, in order to track numerous diseases and conceive effective medication and treatments. Phylogenetic analysis requires large quantities of information to be analyzed and processed for knowledge extraction, using suitable techniques and, nowadays, specific software and algorithms, to deliver results as efficiently and fast as possible. These algorithms and techniques are already provided by several free and available frameworks and tools. Usually, the process of phylogenetic analysis consists of several processing steps, which define a pipeline. Some phylogenetic frameworks have available more than one processing step, such as inferring phylogenetic trees, data integration, and visualization, but due to the continuous growth in involved data amounts, each step may last several hours or days. Scientific workflow systems may use high performance computing facilities, if available, for processing large volumes of data, concurrently. But most of these scientific workflow systems cannot be easily installed and configured, are available as centralized services, and, usually, it is not easy to integrate tools and processing steps available in phylogenetic frameworks. This paper summarizes the thesis document of the FLOWViZ framework, which main goal is to provide a software integration framework between a phylogenetic framework and a scientific workflow system. This framework makes it possible to build a customized integration with much fewer lines of code, while providing existing phylogenetic frameworks with workflow building and execution, to manage the processing of great amounts of data. The project was supported by funds, for a student grant of FCT - NGPHYLO PTDC/CCI-BIO/29676/2017 and an IPL project - IPL/2021/DIVA.