This evolution goes, and must go, hand in hand with advances in diagnostic and monitoring methods, among which non-destructive technologies (NDTs) play a particularly important role. Non-destructive techniques provide insights into the material composition and structural integrity of cultural heritage objects without causing any damage. Together, these technologies facilitate a deeper understanding of historical artefacts and contribute to their preservation by enabling precise, well-informed interventions, without compromising their integrity [4]. Then, NDTs are crucial for the analysis and conservation of cultural heritage artefacts. Among the primary NDTs, those mostly used in this field, also thanks to the existence of portable equipment, are X-ray Fluorescence (XRF) for elemental analysis of materials without sampling need [5], infrared reflectography, useful for the individuation of underlying layers in paintings [6], thermography and ultrasound testing for the detection of structural anomalies [6; 7], Magnetic Resonance Imaging (MRI) for in-depth analysis of organic materials like textiles and wood [8], Ultraviolet (UV) photography to reveal details not visible under normal lighting conditions [9] and multispectral imaging employed to capture images across different reflectance wavelengths [10]. Many of these techniques are imaging-based, meaning that their results can be compared with photographic images and with what is visible to the naked eye. However, sometimes the features revealed by these methods are difficult to precisely locate, due to the large dissimilarity between visible aspects and hidden features collected, making comparisons challenging. This issue makes the ability to accurately overlay diagnostic data onto an accurate 3D model of the studied artwork, building, or object, particularly valuable. In this context, laser-induced fluorescence (LIF) has proven to be a very powerful NDT. LIF, employing a UV laser (over 250 nm) as a light source to excite specific molecules within a sample, is highly sensitive and allows for the precise detection of different classes of materials, both organic and inorganic. Compared to UV photography, LIF offers higher specificity and sensitivity across a much wider range of substances. Initially developed as a point-based method for chemical analysis, LIF has since been integrated with scanning systems, leading to the development of LIF imaging instruments. In recent years, LIF has yielded promising results in the field of cultural heritage, such as detecting materials not visible to the naked eye due to restoration actions [11] or identifying microorganisms in areas where biodegradation is not evident, suggesting the potential for early detection [12]. In fact, several molecules are active in the fluorescence, in particular organic cyclic, polycyclic, heterocyclic and with conjugated double bonds compounds, and some smaller inorganic molecules, such as CaSO\({}_{4}\), CaCO\({}_{3}\), TiO\({}_{2}\), ZnO, and CaC\({}_{2}\)O\({}_{4}\). Thus, LIF is particularly suitable, in the field of CH characterisation, to study dyes, natural and synthetic polymers, such as paper, wood, binders, modern consolidant and protective materials, biological pigments (such as chlorophylls and carotenoids), some stones (mainly calcareous ones), and only a few inorganic pigments (mostly white ones) [11]. It is then clear that comprehensive results can be joined when LIF data are complemented with those from other NDTs, such as Raman spectroscopy, colourimetry, and infrared reflectography, able to identify non-fluorescent materials. Moreover, the interpretation of the fluorescence maps can be challenging without a correlation with visible and structural information. The fusion of LIF data with 3D point clouds introduces a new way to analyse artworks, correlating invisible with visible information. It is well established that the combination of different NDT methods is essential to enhance the understanding and accessibility to CH objects and sites, their health state, and potential risks.