The site of ‘Grotta Poesia’ is one of the richest repositories of filiform post-Paleolithic rock art in southern Italy, as well as the largest archive of Messapian inscriptions known. In 2022, research activities in the field were resumed thanks to the «DigiRock» project, of which objectives, methods and preliminary results are presented in this report. The project’s overarching aim is to develop an artificial intelligence algorithm for recognizing and classifying the engravings found in ‘Grotta Poesia’. The first goal of the project was a 3D scan of the cave using a Terrestrial Laser Scanner (TLS) so as to reconstruct the cavity's floor plan, cross sections and obtain the basic topography, but also to test the accuracy of the TLS in the three-dimensional acquisition of engravings. In order to study the signs engraved on the cave walls and to train an AI algorithm capable of recognizing and classifying them, surveys for digital image acquisition were planned. Using Structure from Motion (SfM) and Multi-view Stereo (MVS) technology, it was conducted 3D photogrammetry on the replicas of the cave walls and, more specifically, on the individual engraved signs. Furthermore, another goal of the project was to create a searchable database of Italian rock art spanning from the Upper Paleolithic to the Bronze Age; currently, the ‘reference collection’ includes more than 1,000 figures (painted or engraved) from about 40 different sites, including shelters, caves and mobile artefacts. At present a significant portion of the rock art signs documented at ‘Grotta Poesia’ appears attributable to a period between the Neolithic and the Bronze Age. The conclusions derived from the study and analysis of the current dataset confirm the effectiveness of deep learning techniques, in particular the use of convolutional neural networks (CNN), in the study of filiform rock art from ‘Grotta Poesia’ cave walls.