  The analysis of absorption features along the line of sight to distant
sources is an invaluable tool for observational cosmology, giving a direct
insight into the physical and chemical state of the inter/circumgalactic
medium. Such endeavour entails the accessibility of bright QSOs as background
beacons, and the availability of software tools to extract the information in a
reproducible way. In this article, we will present the latest results we
obtained in both directions within the QUBRICS project: we will describe how
machine learning techniques were applied to detect hundreds of previously
unknown QSOs in the southern hemisphere, and how state-of-the art software like
QSFit and Astrocook was integrated in the analysis of the targets, opening up
new possibilities for the next era of observations.
