Energy-related renovation is an essential component in achieving emission reduction in the building sector and towards climate neutrality. The digital as-built documentation forms the basis for digital inventory, re-planning and renovation of existing buildings. It is indispensable for relieving the backlog of needed renovation. The advancement of the building information model (BIM) method as general requirement for construction projects forces stakeholders to retrieve 3D BIM from existent real-estate. The first step towards digitizing an object is to capture data with sensors, like cameras or 3D scanners. Using techniques from the field of reverse engineering (RE), the geometry and certain attributes are reconstructed and modelled. This yields a virtual representation of the physical object, typically as CAD model or BIM. Today, this RE process, sometimes referred to as “Scan-to-BIM”, is partly put in practice, but involves tedious manual work. Software tools and algorithms together with AI solutions evolve in order to automate and accelerate the digital as-built documentation. This work presents the complete process chain from existing building to 3D BIM. State-of-the-art literature is consulted and examined. Special focus is placed on different sensors and techniques for data capture and their consequent opportunities and enabled downstream applications. This work extends the approach of “Scan-to-BIM” to various sensors and considers the sensor and data fusion. The research points out the need for and potential of a holistic methodology for digital as-built documentation, leaving the assessment of downstream process steps for future work.