Software for the mechanical engineering industry

For over 25 years, we have been developing custom software for the engineering industry. As a long-standing VDMA member and active board member of the "Software & Digitalization" association, we know the industry firsthand.
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Customer since 2012
Customer since 2018
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Customer since 2005
Customer since 2016
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Customer since 2005
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Customer since 2008
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The engineering industry in transition

The engineering industry is under pressure: stagnant production output, rising digital expectations, regulation (CRA, NIS2), and a shortage of skilled workers demand new solutions. Digital service platforms, predictive maintenance, and industrial AI generate recurring revenue, secure institutional knowledge, and accelerate digital transformation.

In practice, typical challenges emerge:

  • Legacy system landscapes: 77% of manufacturing executives report that legacy systems hinder their operational performance.
  • Data silos and fragmentation: Systems like ERP, MES, or PLM operate in isolation rather than in tandem – only 26% of users have full access to the data they need.
  • IT/OT convergence: disparate languages, protocols, and security requirements are driving IT and automation technology further apart
  • Regulatory pressure: As of December 2027, CE marking will no longer be possible without Security-by-Design (CRA). NIS2 has been in effect since the end of 2025. The new EU Machinery Regulation makes security a safety requirement starting in 2027.

Why generic.de is the right software partner for the mechanical engineering industry

We know your industry from hands-on project experience

As a VDMA member and through our many years of collaboration with companies like LEWA, TRUMPF, and Uhlmann, we know how mechanical engineering works – from HMI to IIoT.

You start testing with real users up to 3x sooner

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.

Maintainable and scalable software for years to come

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.

No lock-in – switching is possible at any time

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.

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Moritz Pastow
PROGRAM MANAGER DIGITAL SERVICES & IIOT,
LEWA GMBH
Since everyone is connected and everyone has the same project know-how, it just works. And I save time and costs that would have been spent on explanations, knowledge transfer, management, or coordination.
Julian Geiger
Agile Team Lead Digital Solutions
Uhlmann Pac-Systeme GmbH & Co. KG
We were impressed by how quickly the generic.de team familiarized themselves with the subject matter and the motivation they brought to such a complex topic. The team works very independently and, just like us, places the highest value on quality. This way, the software and our standards fit together perfectly!
Alexander Strobl
DIRECTOR DIGITAL TRANSFORMATION IT
J. WAGNER GMBH
At the beginning, there was a lot of mocking and prototyping involved. You first have to find a service provider who is willing to do that. generic.de simply has the right attitude for such challenges – the perfect hands-on mentality.
Tobias Vock
Manager solutions
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‍Saatmann gmbh
The qualified software audit from generic.de helped us a great deal in the further process. The result took a lot of pressure off us internally. We now had neutral, external confirmation that we were on the right track and knew which levers we still needed to adjust.
Manuel Stuhlinger
APPLICATION ENGINEERING & PRODUCT DEVELOPMENT
BEST WOOD SCHNEIDER® GMBH
For me as a customer, clean code simply offers the security of being independent. I don't want to be stuck in 10 years with a piece of code that no one understands anymore and have to start all over again.
Nora Legittimo
CHIEF DIGITAL OFFICER (CDO),
SCHÖCK BAUTEILE GMBH
I find a beta phase with absolutely no bugs or other issues in the software to be truly unusual. But especially considering our industry, which is extremely safety-conscious, this is obviously a great thing.

How we can support you in mechanical engineering

Person holding a tablet displaying industrial monitoring software with charts and asset information.

IIoT platforms & machine connectivity

Integrating heterogeneous machine fleets – with varying years of manufacture, manufacturers, and control systems – into a unified data landscape. Using OPC UA, MQTT, and edge technology, we lay the foundation for all further steps in digitalization: from condition monitoring to the digital twin.

A man with a tablet operating a machine in a modern factory hall.

Predictive maintenance & condition monitoring

Leverage operational data from sensors and control systems to predict maintenance needs and prevent downtime. Across all industries, unplanned downtime can be reduced by 30 to 50% – using ML models, time-series analysis, and intelligent dashboards.

Automated packaging machine placing boxes on a conveyor belt in a factory.

Modern HMI interfaces for machines and systems

Replace outdated HMI systems with modern, web-based interfaces – responsive, touch-optimized, and fully focused on Industrial UX. The result: shorter training times and fewer operating errors. Plus: configurable HMI frameworks that allow machine builders to assemble their own user interfaces without IT expertise.

Man with glasses looking at large screens with charts and data visualizations.

Digital services: from an after-Sales cost center to a revenue model

Self-service portals featuring spare parts ordering, documentation, ticketing, and remote support – seamlessly integrated with ERP and CRM. The foundation for recurring revenue and stronger customer loyalty in the age of servitization.

Man wearing glasses looking at large screens displaying charts and data visualizations.

AI in quality control: from a 70% to a 99% detection rate

Camera-based inline inspection using deep learning replaces or supplements manual visual inspection. Computer vision and intelligent material recognition deliver consistent results in less than one second per component.

Man wearing glasses looking at large screens displaying charts and data visualizations.

CRA, NIS2, EU machinery regulation: developing compliant software

Starting in 2027, the CE marking will require security-by-design. We integrate SBOM generation, vulnerability management, and secure development processes directly into the delivery pipeline – no costly rework, just compliance from the start.
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Our references

Selected case studies

LEWA GmbH

Development of an IoT platform with smart monitoring

How we are supporting LEWA GmbH in minimizing pump downtime and maximizing energy efficiency through Industrial IoT and smart monitoring.
  • Smart monitoring enables automated diagnostics and predictive maintenance
  • Reduction of administrative and organizational overhead
  • Unique customer experience
Clip closure machines

AI-supported process control

How we are enabling a mechanical engineering company for clip closure technologies to achieve fully automated quality control using AI.
  • Automated inline quality control instead of sporadic visual inspection
  • Fewer bottlenecks, downtimes, and system risks
  • Full transparency and scalable development
Uhlmann Pac-Systeme GmbH & Co. KG

Development support: quickly onboarded & clean code

How we supported the Uhlmann Group in the development of their "Track & Trace" software with several Clean Code developers.
  • Rapid familiarization with the domain thanks to many years of industry experience
  • High software quality thanks to a Clean Code approach
  • The generic.de team is a fully integrated part of the development team at Uhlmann
Mechanical engineering company (Ditzingen)

Machine control software with a modular HMI framework

How we supported a mechanical engineering company in developing an HMI framework for a series of 3D laser machines.
  • Uniform, intuitive user interfaces
  • Modularly configurable, depending on the machine and use case
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Typical challenges in software ­projects – and how we solve them

Challenges & Solutions

Unclear project scope: It is difficult to estimate the scope, timeline, and budget before the project starts.
Upstream concept development: Assess risks and develop a reliable cost estimate – before development begins.
Lack of prioritization: Too many features, too little focus – in the end, a lot is started, but nothing is truly finished.
Dual Track Agile: Parallelizing conception and development – continuously prioritizing features based on business value.
Increasing compliance requirements: CRA, NIS2, ISO 27001 – regulatory pressure is growing, and retrofitting security is expensive.
Security-by-Design: Security and compliance requirements are integrated into the development­process from day one.

How we develop your mechanical engineering software

DESIGN
Process Analysis & Ideation
1-2 weeks

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.

DISCOVER
Concept Development & Knowledge Graph
4-8 weeks

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.
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DEVELOP
AI-driven Software Development
6-X months

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.

DEVOPS
Support & Maintenance
continuously

We operate and maintain your software, monitor system performance, and ensure sustainable, secure operation through regular updates and ongoing technological development.

Your benefits

AI-driven development makes coding up to 3x faster

AI-driven software development accelerates implementation – standards and clean code ensure that speed does not come at the expense of maintainability.

Over 25 years of enterprise experience

For over 25 years, we have been developing custom software for the industrial sector, combining deep industry expertise with a collaborative, peer-to-peer approach.

No hidden Lock-In

The source code, concepts, designs, and AI development environment belong to you – they are readable and can be further developed with other partners at any time.

We protect your investment with Clean Code

Whether using AI or done by hand – Clean Code is our standard. This ensures that your software remains flexible and expandable even years down the road.

Software development in Dual Track Agile

Design and development proceed in parallel – only what has been validated and generates added value is developed.

Compliance-driven development

ISO-compliant processes and CRA readiness are built in – compliance from the start, not as a costly add-on.

User-centric design from the start

Prototypes and usability tests before any code is written – for software that users embrace and that delivers a return on investment.

Experts in every project role

Our employees are experts in their fields, receive ongoing training, and have a generous annual training budget.

API-first

Clearly define interfaces so that ERP, MES, and machines can work together seamlessly and scalably.

Your entry into mechanical engineering software: just a phone call away.

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Jörg Lenz
Key Account Manager
faqs

Frequently asked questions about software projects in mechanical engineering

When is a custom software project in mechanical engineering economically viable?

Such a project is worthwhile if you want to achieve measurable improvements – for example, in machine availability, service costs, time-to-market for new variants, or in developing data-driven revenue models.
Typical benefits include fewer unplanned downtimes, more efficient maintenance, faster commissioning, or a digital service offering that strengthens customer loyalty and recurring revenue. Often, a clearly defined starting point – such as a pilot for a specific machine series or a concrete service use case – is sufficient. It’s important to define benefits and key performance indicators early on.

How do we handle an evolved system landscape – does everything need to be rebuilt from scratch?

Generally, no. Many solutions connect to existing systems and extend them in a targeted way – such as control systems, SCADA, ERP, MES, or existing service tools. Older machines and controllers can also be integrated using open standards like OPC UA and MQTT. Instead of creating parallel, isolated solutions, we recommend a step-by-step expansion of your existing landscape to ensure the solution remains maintainable and integrated in the long term. The key is a clean architecture that bridges the gap between old and new.

What role do the CRA, NIS2, and the new EU Machinery Regulation play for our software?

An increasingly central one. Starting in December 2027, the Cyber Resilience Act will require “security by design” as a prerequisite for CE marking – including mandatory SBOMs and vulnerability management for at least 5 years. NIS2 has been in effect in Germany since the end of 2025 and affects approximately 29,500 companies. The new EU Machinery Regulation explicitly makes security a safety requirement starting in 2027. Anyone developing or modernizing software now should plan for these requirements from the very beginning. We integrate compliance requirements directly into our development processes – no costly rework.

For which departments is the topic of software most relevant?

Software projects in mechanical engineering are not purely an IT matter. Typical stakeholders include product development, service/after-sales, application engineering, production, and, of course, IT. Profitable projects emerge where domain expertise and IT knowledge come together early on. In our experience, clear roles and short decision-making paths are more important than mere organizational assignment. Our “Product Trio” approach (Business + UX + Technology) ensures that all perspectives are integrated from the very beginning.

What exactly does “servitization” mean and do we need custom software for it?

Servitization describes the shift from simply selling products to data-driven business models: Equipment-as-a-Service, pay-per-use, remote monitoring, and digital after-sales platforms. Off-the-shelf software often reaches its limits here because the business models must be closely integrated with machine logic, customer processes, and the existing IT landscape. Custom software can bridge exactly this gap – between the machine, the data, and the new business model.

What should be the scope of an initial software project in mechanical engineering?

Small and clearly defined: a manageable use case with recognizable benefits – e.g., defined processes, a pilot customer, or a clear service use case. The goal is to quickly gain sound insights and experience with technology, organization, and interfaces. Starting this way reduces risks and makes it easier to assess the actual benefits. Afterward, the software can be expanded in a targeted manner – to include additional processes, regions, data sources, or functions.

What internal resources does a typical software project require?

Typically, this includes contacts from product/development, application engineering or service, IT, and – if necessary – maintenance or quality assurance. What matters most is not so much the team size as clear responsibilities and decision-making processes. Domain and process knowledge is just as important as expertise in integration and operations. Regular communication among all stakeholders contributes significantly to the project’s success.

How long does it take to implement such a software project?

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 the effort required and define the roadmap.

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Industrial AI: 20 real-world use cases

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.

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Industrial AI: 20 real-world use cases