To represent the built environment consistently, digital models that accurately capture both geometry and topology are becoming increasingly relevant. The amount and variety of geometric data in architecture, civil engineering, and geodesy requires sophisticated algorithms for modeling and assessment, at the moment especially for export, validation and repair. Although many existing tools cater to specific modeling needs, they often fall short of providing a comprehensive solution that encompasses both geometric and topological elements into one methodology. Space partitioning, a method well-documented in literature, emerges as a robust technique for representing a diverse array of geometric domains, from simple to complex structures. The proposed space partition concept organizes the entire Euclidean space into distinct, non-overlapping point sets. A space partitioning platform based on topological spaces operates mainly through two atomic actions: splitting a domain into two parts and merging adjacent domains of the same dimension. These are referred to as work steps. Recognizing the widespread application of parametric design in building projects, this paper introduces first findings on how established parametric design functionalities can be aligned with these fundamental work steps for space partitioning, thereby creating a unified modeling approach that enhances consistent modeling capabilities. This integration not only simplifies the modeling process but also ensures the consistency of spatial models, eliminating the need for conventional geometric validations such as clash detection. Initial results have promisingly demonstrated that energy analysis and city modeling are suitable application areas, as faulty topology of models often represents a common source of error in these fields. While the present study focuses on modeling planar surfaces, it underscores the potential for applying parametric design methods within the partition platform to comprehensively address the geometric requirements across architecture, civil engineering, and geodesy. This approach offers a promising avenue for developing digital models that are both accurate and efficient, facilitating better design and navigation within the built environment.