Machine tools are becoming increasingly powerful, but competition is increasingly decided by software: by the user interface, serviceability, and how quickly a new machine variant can be delivered. Standard platforms reach their limits here because they cannot accommodate the variety, the proximity to control systems, and the lifecycles of this industry.
In practice, typical challenges emerge:
For machine tool manufacturers, the real competitive advantage arises when software does more than just operate the machine—it creates shorter setup times, predictable service, and new digital revenue streams.
Through our long-standing partnerships with companies like TRUMPF and Klingelnberg, we have gained a deep understanding of the machine tool industry – from HMI development to service management.
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.
One user interface for an entire machine series instead of a separate solution for every machine type: We design and develop modular HMI frameworks that adapt to different display sizes, equipment variants, and user roles. Setup, programming, diagnostics, and maintenance each get the view they need – consistent across the entire product line. The result: shorter training times, fewer operating errors, and a unified brand experience at every machine.
From the initial call to the final report in one system: We develop service management solutions that coordinate technical customer support throughout the entire machine lifecycle – including 24/7 ticketing, deployment planning, spare parts procurement, and integration with SAP, CRM, DMS, Active Directory, and telephony. The result: predictable service instead of reactive operations – and reliable data for service quality and after-sales revenue.
High numbers of variants can no longer be documented manually. We develop configurators that generate the exact CAD model and dimension document from a product configuration just in time, parallelize calculation procedures, and digitize processes in application engineering – globally deployable and integrated into the existing system landscape. The result: quotes and engineering documents in minutes instead of days, with no media discontinuity between sales, application engineering, and design.
Make tool usage, spindle load data, and process flows transparent – across individual machines, lines, and locations. All data regarding the machining process, tools, and machines is consolidated in a single web application, with rules that monitor critical load values and trigger notifications. The result: faster root cause analysis for anomalous parts or batches, reliable tool life evaluations, and a knowledge base that is shared across the company rather than locked away with individual experts.
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.
A standard platform is the right choice if the machine fits its operating logic and protocol ecosystem: faster rollout, lower implementation risk, and a familiar interface for maintenance. Custom operating software is worthwhile when the operating concept becomes a key differentiator for the machine, when interface and database solutions must remain flexible, when per-machine license costs impact unit costs, or when a single interface needs to support an entire product line. The most common objection to custom software is the dependency on individual specialists for maintenance. This risk arises from a lack of standards, not from custom development: clean code is our company standard, ensuring your software remains adaptable even ten years from now.
Usability usually suffers when an interface is designed from a technical perspective rather than from the workflow: the look may be more modern, but setting up, programming, or switching between offsets requires more steps than before. This can only be prevented before implementation. That is why we create wireframes, click-dummies, and conduct usability tests before any code is written. Each increment is followed by user testing, and the operating personnel see the product long before the go-live. In a similar project, this measurably reduced training effort, operator errors, and measurement inaccuracies.
Through a modular HMI framework. Common components such as navigation, permissions, diagnostics, or parameterization are centralized, while machine-specific modules are added as needed. The interface and controls adapt to different display sizes. This way, your customers operate every machine in your series using the same pattern, and you maintain one software base instead of a chaotic sprawl for each machine type.
Yes, usually step-by-step rather than through a complete rewrite. The hardware-related portion, validated over years, is the most expensive and riskiest to rewrite. We encapsulate it behind a defined interface and modernize everything around it first. It is replaced piece by piece, with pre-agreed criteria for behavioral parity, and every step is deployable. Where knowledge resides only in a few heads, we document the behaviors that must be preserved before replacing them and secure them with tests. Existing WPF applications are not automatically legacy – switching to current .NET is often the lowest-risk first step. If the existing system can no longer support the requirements, a new design is more cost-effective than further patching: that was exactly the case for a configurator that had grown over 30 years.
Yes. We have experience integrating controllers, sensors, and measurement hardware via OPC UA, fieldbuses like Profinet and Profibus, as well as proprietary interfaces. Machine and process data are processed efficiently and transferred to MES, ERP, CAQ, or cloud platforms. Existing infrastructure is not replaced wholesale but rather integrated into a cohesive software landscape.
Typical points of contact include product/development, application engineering or service, IT, and, if necessary, maintenance or quality assurance. The team size is less critical than having clear responsibilities and decision-making paths. Technical expertise is just as important as know-how regarding integration and operations. Regular communication between all stakeholders contributes significantly to success.
Through a dedicated, limited phase prior to development. Our preliminary concept development lasts between two and twelve weeks and concludes with a validated solution concept, click-dummies, a prioritized backlog, and an implementation plan. We classify requirements beforehand so it is clear which parts of a proposal are reliable and which still require research. A fixed price for an unclear scope is merely an illusion of security – a fixed budget with a flexible scope is more sustainable. The development itself takes anywhere from a few months for focused enhancements to multi-year timelines for group-wide frameworks or the replacement of legacy platforms, depending on the scope and depth of integration.
With the Cyber Resilience Act, mandatory requirements will apply from 2027 that affect the entire development process, not just the finished product: a Software Bill of Materials, documented vulnerability management, and update capabilities throughout the product lifecycle. Depending on the field of application, ISO 9001, IATF 16949, NIS2, as well as audit trail and data integrity requirements may also apply. Anyone who waits until 2027 to adjust their development processes will be too late. We therefore integrate security and compliance requirements into architecture and delivery from day one, rather than patching them on later.
Small and clearly defined: a manageable use case with recognizable value – e.g., specific measurement processes, a pilot customer, or a clear service use case. The goal is to gain quick, well-founded insights and experience with technology, organization, and interfaces. Starting this way reduces risks and makes the actual value easier to evaluate. Afterward, the software can be expanded in a targeted manner – adding more processes, machines, regions, data sources, or functions.
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.
Both paths are possible, and the decision doesn't have to be made at the start of the project: we can handle operations, maintenance, and further development – or your team can do it themselves, gaining the necessary skills during the project through clean code workshops, on-the-job training, and the establishment of a product owner role. In a similar project, the client is now continuing to develop their software with their own internal team. Contractually, both cases apply: you are never locked in with us; exit clauses and escrow are standard.
AI in industry is no longer a topic for the future, but where is it really worth getting started? This whitepaper presents 20 anonymized real-world examples of where AI is delivering measurable value in core processes today – from quality assurance and predictive maintenance to intelligent production planning.
