SCHÖCK BAUTEILE GMBH
Weak productivity growth¹, a shortage of skilled workers, and increasing demands for digital collaboration require new solutions. Cloud software, BIM, and AI create efficiency – yet many companies are not yet prepared for end-to-end digital workflows.
In practice, typical challenges emerge:
Through our long-standing partnerships with companies like Schöck, Vollack, and best wood Schneider, we know how the construction industry works – from structural design logic to BIM.
Thanks to our AI-driven software development, we deliver features up to 3x faster. You can start testing sooner and get real user feedback earlier – while changes are still cost-effective.
We are convinced that even in the AI era, industrial software must run for decades. That is why our clean code standard applies to AI-generated code as well. For sustainable, not disposable software.
The source code, concepts, designs, and the AI development environment belong to you. You could continue working with your own team tomorrow. We keep clients through results, not lock-ins.

Make construction products digitally plannable with integrated calculation, modular architecture, and centralized release management. AI integrations allow existing cloud applications to be intelligently expanded and agentically controlled, for example, for calculation suggestions or plausibility checks.

Replace legacy Windows applications with web-based interfaces – platform-independent, with global versioning and no manual update effort. Through AI integrations (e.g., via MCP), specialized applications can be retrofitted with intelligent features without touching the core logic.

Digitally inventory, locate, and maintain the operational readiness of construction equipment and vehicle fleets. Using sensors, telematics, and IoT platforms, you can reduce search times, downtime, and inefficient utilization – from individual construction sites to fleet management.

Automatically identify and classify materials, documents, or components using image recognition, NLP, or machine learning. Where manual assignment is too slow, AI models create structured data from unstructured sources.

Digitally mapping buildings throughout their lifecycle – from planning and operation to management. We develop platforms that centrally bundle building data and integrate processes such as maintenance, energy management, or tenant administration.

Transforming ERPs, planning tools, BIM models, and manufacturer platforms into a seamless architecture. We connect your systems using an API-first approach and open standards. For companies that are not yet BIM-ready, we first create the necessary interfaces as a foundation.
Together, we analyze your processes and identify your use cases. From there, we develop ideas for software solutions. If you already have a specific idea, we evaluate it for business viability and technical feasibility.
We design your software solution at the intersection of biz, tech, and user requirements. The result is a sophisticated solution concept structured as a machine-readable knowledge graph – perfectly suited for development with AI agents.
Development in Dual Track Agile: In our AI development environment, AI agents handle routine tasks, code, and testing according to clean code standards. Our experts continuously design, verify, and enrich the knowledge graph.
We operate and maintain your software, monitor system performance, and ensure sustainable, secure operation through regular updates and ongoing technological development.
Digital ecosystems in the construction industry generally consist of numerous specialized systems – no single software category can fully cover all use cases. When data from ERP, inventory, localization, and construction site management needs to be consolidated, custom software is often the only option to avoid media discontinuities. Tailor-made software is particularly advantageous when mapping individual products or processes.
A typical approach involves four essential steps: (1) Developing a target vision, (2) Inventory assessment (equipment, systems, data silos), (3) Developing a system architecture, and (4) Identifying potential obstacles (e.g., roll-out, hardware retrofitting, regulations). In construction equipment management, digitalization often begins with inventory tracking (Stage 1) before further steps like IoT localization and connectivity follow.
Localization: less loss and theft, no more long searches for equipment. Operational readiness: telematics, predictive maintenance, and optimized workflows. Empirical data shows, for example, up to 20% fewer miles driven and up to 40% fuel savings per vehicle. Connectivity: device-to-device communication, remote control, and robotics support.
Through methods like Dual Track Agile and rapid prototyping, early validation points are standard. Interactive showcases and MVPs can often be presented after just a few weeks, depending on the project scope.
Whether a complete rebuild is necessary depends on factors such as technical dependencies or the desired level of innovation. A step-by-step, customized approach is often more sensible than a "big bang" transition.
Yes – by intentionally separating the backend and frontend, new features can often be integrated into existing software environments, allowing structural engineers to continue working as usual.
The duration depends heavily on the scope, the existing system landscape, and the integration effort – ranging from a few months for focused enhancements to longer timelines for comprehensive platforms or numerous interfaces. Pilot projects provide reliable results early on and help to realistically assess effort and roadmaps.