As of 2020, every new building in the European Union will have to reach the nearly Zero Energy Building (nZEB) performance. However, building nZEB will not be sufficient to reach carbon neutrality in 2050 as required by the last IPCC report: indeed, even nZEB consume energy due to their embodied impacts. Thus, life-cycle assessment will become a mandatory approach to mitigate environmental impact of buildings beyond the nZEB performance. However, the complexity of Life-Cycle Assessments (LCA) continues to make it difficult for it to be effectively used at the early design stage. A promising theoretical framework called LCA-based data-driven method had been proposed in prior work by the authors to tackle these issues (Jusselme et al. 2018a). This paper presents the prototype that has been built for the developed method to be tested in a first application. The case study chosen for this application is the future building of the smart living lab in Fribourg, which aims to reach the SIA2040 performance threshold. A specific knowledge database of 20’000 design alternatives – with a LCA performed for each of them – was thus generated with a parametric approach. First, the method provides sensitivity indices so as to better understand the influence of different design parameters. Second, performance target values are provided at the building component level in order to choose building techniques and materials in accordance to the SIA2040 objectives. Ultimately, the method offers site-specific guidance with an exploratory perspective. By literally exploring a database of design alternatives generated specifically for that site and urban context, the user (designer) gets valuable insights about the choices still available when other decisions are made if the SIA2040 performance ambitions are to be kept. In comparison to current practices, this case study demonstrates the ability of the method to provide a highest amount of design insights beyond the simple assessment process, in a shorter time. Further research needs to be carry out to verify the benefits of the method in the frame of a real design process, thanks to practitioner’s evaluations and feedbacks.