Our services apply where planning results are not only drawn, but also structured, reviewed, modeled, and transferred into digital workflows.
The register structure serves as a fast introduction to operational planning, modeling, and data processes.
Plan versions, technical drawings, and model development.
Information models, attributes, and coordination.
Spatial data, location references, and geospatial analysis.
Early analysis before design and technical definition.
Interfaces, APIs, and recurring processes.
Scans, PDFs, and re-vectorization of legacy plan versions.
We create and revise CAD data when plans need to be technically reliable, cleanly structured, and directly reusable — from precise 2D foundations to 3D models for design, execution, and documentation.
Under time pressure, plan versions often emerge that work in the short term but later make coordination, review, and further processing more difficult. We clean up geometries, layers, layouts, references, blocks, dimension chains, and updates so that working versions become reliable project foundations again. We pay attention to clear plan logic, clean file structures, traceable revisions, and preparation that can either be continued internally or safely handed over externally.
CAD data must do more than represent geometry. It must be clearly readable, reviewable, versionable, and connectable — for specialist planning, engineering, plant construction, manufacturing, documentation, and later handovers. That is why we treat plans not only as drawings, but as a technical information base: with clear layers, consistent references, reliable dimensions, and a structure that remains understandable even after several project phases.
BIM only becomes usable when geometry, component information, and model structure work together. We build, review, and maintain models so that they can be coordinated, evaluated, and handed over to other project participants without data breaks.
A spatial model is not yet a reliable BIM model. The decisive question is whether components are correctly classified, whether attributes are maintained consistently, and whether the model structure works for coordination, quantities, handovers, and later evaluation. We review not only visible geometry, but also object logic, information content, naming conventions, model setup, and whether the data can actually be used in the next process step.
We review the typical breaking points in the BIM process: missing attributes, inconsistent classifications, incorrect object logic, unclear IFC exports, or models that look right visually but cannot be evaluated professionally. The goal is a handover in which information does not have to be manually reinterpreted, but continues reliably in coordination, quantity takeoff, quality assurance, and documentation.
GIS makes spatial dependencies visible before they become expensive in the project. We prepare geodata so that location, area, infrastructure, terrain, environmental factors, and usage conflicts can be evaluated professionally.
Many relevant planning risks lie outside the building or object: terrain, access, climate, neighborhood, protection zones, area references, or usage conflicts. GIS brings these layers into a reviewable context. This makes dependencies visible that are often noticed too late in conventional plans — such as elevation references, clearance areas, overlaps with infrastructure, environmental restrictions, or conflicts between existing conditions and planned use.
A map is only the visible result. What matters is the data logic behind it: relevant layers, reliable overlays, clear spatial references, and evaluations that do not merely illustrate decisions, but justify them. We ensure that datasets are derived transparently, located geometrically correctly, and structured in such a way that they can be reused for variants, approvals, reports, and technical coordination.
Pre-design reviews the foundations before design decisions are fixed. Location, climate, use, life cycle, materiality, and technical requirements are analyzed early so that assumptions do not have to be corrected expensively in later service phases.
Many projects make design decisions before location data, usage scenarios, technical dependencies, or life-cycle questions have been sufficiently reviewed. Pre-design moves this review to the point where changes are still controllable. This means variants are compared not only aesthetically, but evaluated based on reliable parameters: climate, orientation, access, space program, technical feasibility, material strategy, and long-term use.
Orientation, climate, use, materiality, energy demand, and life cycle are not treated as side issues, but as concrete planning parameters for reliable variants, better decisions, and fewer later corrections. We translate context into reviewable foundations: which assumptions hold, which risks become visible early, and which technical consequences arise from location, program, and use.
Wherever CAD, BIM, or project data is repeatedly read, written, checked, or transferred, errors, media breaks, and unnecessary effort arise. We translate such workflows into stable digital processes, scripts, and interfaces.
Automation makes sense when it measurably removes friction from the project: less manual repetition, fewer copy-paste errors, more consistent data versions, and clearer workflows between planning, review, and handover. That is why every automation starts with process logic: Which data is needed, where do errors arise, which rules can be clearly mapped, and at what point does a script actually save time, questions, or corrections?
Many digital processes do not fail because of the individual software, but because of the transitions: wrong formats, manual exports, unclear responsibilities, or inconsistent data versions. We look at the entire data flow between tools, disciplines, and project environments. This results in practical interfaces, checking mechanisms, and small, robust tools that fit existing workflows instead of creating new isolated solutions.
Old paper plans, scans, or PDFs are often the only available foundation — but not yet a reliable working basis. We convert analog or unstructured existing documents into clean digital CAD structures that planning can continue working with precisely.
A scan shows information, but it is not yet a reliable planning foundation. Only when scale accuracy, geometry, layer logic, labeling, and plan structure have been cleanly reconstructed can existing conditions be used professionally again. We distinguish between visible information, plausible reconstruction, and open ambiguities so that later planners know which data is reliable and where existing conditions need to be checked.
Re-vectorization is not merely diligent manual work, but project preparation. It creates the foundation on which CAD, BIM, and engineering processes can cleanly build — without constant questions, retracing, and correction loops. The better existing conditions are digitally structured, the more reliably conversion planning, technical review, quantity takeoff, model creation, and later documentation function.