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Industrial AI Solutions

Fewer pilot projects, more systems and processes that perform measurably better.

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HomeServicesData & AIIndustrial AI Solutions

Industrial AI solutions built to withstand the rigors of everyday factory operations

AI has long been in use in industry, and its scope of application continues to grow. However, our study on technology efficiency also reveals the flip side: 19% of respondents still see no tangible business value from AI. A pilot project merely proves that something is possible.

Between the pilot and full-scale production lies the reality of industrial operations: sensor data from multiple generations of machines, a network that no one is allowed to tamper with, and a facility that runs around the clock. Add to that the challenge of gaining internal buy-in: production, IT, and maintenance must all be on board with such a project. That’s exactly where we come in.

We build industrial AI solutions tailored to your value chain: in manufacturing, quality control, maintenance, and the product itself. First, we determine which use case makes the most sense for you. Only then do we discuss the technology.

Less Technology. Better Business.

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Why Industrial Companies Partner with Us to Implement Their AI

OT and IT Under One Roof

We integrate machine and process data from the production floor with your IT systems, including real-time integration and network isolation. Pure IT consulting firms rarely offer this.

Database included

If your data set is incomplete or disorganized, we’ll get it in order first. Where others suggest trying again later, we’ll get you ready to go.

AI in the system and on the device

Your model runs where it belongs: in the cloud, on the production line, or on the control system. This way, you retain control over latency, bandwidth, and data sovereignty.

Set Up and Hand Over

After a guided hypercare phase, you’ll operate the solution on your own, using runbooks that your team has tested in production. No lock-in, no long-term commitment.

An abstract illustration depicts a human figure made up of geometric shapes in a pattern of pink and purple.
“The AI Assistant provides our purchasing department with a shared knowledge base. It’s the perfect starting point for searching worldwide for the suppliers best suited to each production site and product group. This strengthens ifm’s global procurement capabilities. New employees can use it to conduct targeted searches right away. Subjective experience no longer influences the search for suppliers. Data that was previously scattered across ERP systems or fragmented databases is now consolidated here.”
Manuel Vetter, Director of IT Infrastructure Services at ifm

Where Industrial AI Pays Off Today, and Where We Advise Against It

The greatest leverage lies where your systems are already generating data and an effect can be measured. Predictive maintenance consistently ranks first among the potential benefits of AI in industry, but it particularly often fails due to this very prerequisite: the quality of the available data is rarely sufficient. Where either of these is missing, the project becomes a costly experiment.

Field of Application

What It Requires

Predictive Maintenance on Equipment

Historical data spanning multiple outages, not just instantaneous values. If the historical data is missing, we'll build it up first.

Product Quality Inspection

Sufficient image data showing known defect patterns and a camera synchronized with the line.

Process Anomalies

A process whose normal state can be described. In that case, AI can also detect errors even without an existing rule.

Knowledge and Documents at the Plant

Well-maintained documents and clearly defined access rights. That’s the foundation on which we build search and assistance for your employees.

On the shop floor, AIoT solutions for manufacturing build AI directly onto the existing machine network. AI-based defect detection identifies product defects right on the production line, rather than waiting until final inspection.

We advise against it if a clear set of rules can deliver the same benefits more cheaply and transparently. We rarely halt an entire project, but we regularly stop an initial phase that is too ambitious. Two use cases visible internally are usually the better starting point because their benefits can be verified in-house.

Our References and Projects

How can a legacy system be replaced while ensuring business continuity? Our case studies provide insight into projects in which outdated structures were transformed into high-performance, future-proof systems.

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What Sets Industrial AI Apart from Office AI

A language model that incorrectly summarizes a bill costs one correction. A model that incorrectly assesses an investment costs one shift. Five key differences determine who can carry out such a project.

It's different in the industrial sector

What that means for us

An error doesn't stay on the screen; it leaves a line behind.

We build steps that can be taken one at a time, rather than promising autonomy.

The data comes from control systems, sensors, and SAP, not from documents.

OT and IT integration is our core competency, not just an add-on.

The evaluation often has to take place in sync with the machine.

In that case, the model runs on the device instead of in the cloud.

Machine data is your expertise—not just a data set.

Raw data remains at the plant upon request, and operations are independently managed within Europe.

Ultimately, it's up to your maintenance department to take action.

The individual remains part of the review process; your team helps make decisions and takes over operations.

You can use this as a benchmark to evaluate any other provider. Ask who is familiar with your control systems, who is helping to build the database, and who will be operating the solution in two years. If any of these answers are vague, it will end up costing the plant a lot of money.

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Which use case will pay off first at your plant?

We evaluate your use cases in the AI Readiness Check and identify the obstacles.

Book an appointment now

Industrial AI in the plant and embedded AI in the device

Not every model belongs in the cloud. Latency, bandwidth, and data sovereignty often make it a poor choice, especially when the machine needs to react immediately to the result. That’s why we plan for computing right from the start.

Embedded AI systems for industry solve exactly this problem: Small ML models—and, when needed, language models—run directly on the device or on the control system. This keeps your raw data right on the factory floor.

In most cases, a combination of both is the right approach. Analysis at the machine ensures fast response times, while analysis on the platform provides a view across production lines and locations. Only as much data as this comparison requires is sent to the cloud. We’ll determine the right balance for your specific case before we begin development.

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Industry 4.0 Consulting

Broader digitalization of your production—from connecting equipment to software on the factory floor. The first step when AI isn't yet a priority.

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AI Consulting

Before implementing AI, determine whether and for what purposes it is worthwhile for your organization. The result will be a prioritized roadmap rather than a catalog of tools.
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IIoT Platform

The data foundation for AI: Connecting machines, standardizing values, and making locations comparable. A prerequisite for most use cases.
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Digitalization in Manufacturing

A comprehensive view of your entire manufacturing process, from planning to shop-floor applications. It shows where artificial intelligence can be usefully applied down the line.
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Here's How We'll Get Your First Industrial AI Project Off the Ground

The first step is a small one and provides a basis for decision-making. It starts with the AI Readiness Check, which can be run on your production data instead of demo data if you prefer. After that, you decide whether and how to proceed. The first step is a small one and provides a basis for decision-making. It starts with the AI Readiness Check, which can be run on your production data instead of demo data if you prefer. After that, you decide whether and how to proceed.

Phase

Result

AI Readiness Check

Evaluated use cases, identified barriers, and a recommendation for how to proceed.

First Phase of Expansion

A productive solution for a production line or a facility—not a prototype that will be discarded later.

Handover

Your team manages operations independently, using proven runbooks and assigned roles.

Work is carried out by a mixed team consisting of your experts and our developers. Your maintenance staff and process experts help decide which results will be most useful in day-to-day operations. We consider AI that no one uses on the factory floor to be a failure, and that is exactly how we measure success.

We don’t promise you a self-managing factory. We build the steps that make sense today, and we won’t take the next step until the previous one has been proven effective.

Two people are discussing a project on a laptop.
Its first phase of implementation—in production rather than as a pilot.

We build them as a cross-functional team and hand them over along with proven runbooks.

Book an appointment now

Frequently Asked Questions About Industrial AI Solutions

  • Can we transfer an AI solution from administration to production?

    It’s rarely a one-to-one match. Models can be adopted, but data integration cannot: In administration, data is stored in documents and office applications; in production, it’s stored in control systems, sensors, and SAP. Those coming from the world of general-purpose AI solutions for businesses are primarily rebuilding the path from the machine to the analysis.

  • What Are Embedded AI Systems for Industry, and When Are They Worth It?

    Embedded AI systems for industry are AI models that run directly on the device or control system rather than in the cloud. They are worthwhile when response times in the millisecond range are critical, bandwidth is limited, or raw data must not leave the factory premises. Small ML models can be operated there for over ten years.

  • What programming languages does MaibornWolff use for industrial AI solutions?

    MaibornWolff does not limit itself to specific programming languages when it comes to industrial AI solutions. The programming language is determined by the solution, not the other way around: What runs on a controller has different requirements than an analysis performed in the data platform. Success depends on the layers above—namely, data connectivity, architecture, and operations. We select the programming language in collaboration with your team so that your employees can continue to develop the solution themselves later on.

  • What platforms and technologies does MaibornWolff use for industrial AI solutions?

    MaibornWolff operates independently of any specific vendor and selects the platform and technology based on your specific use case. We are certified by or partnered with the major cloud and data platforms, and we also offer a European-based option for enhanced data sovereignty requirements. We are certified company-wide to ISO 27001 and ISO 9001.

  • How much effort should we expect a project involving industrial AI processes to require?

    The effort required for industrial AI processes depends on the data available, the machinery, and the desired outcome; that’s why we start with an assessment within a predictable framework. Two factors are most commonly underestimated: the internal effort required on your end and the integration of existing systems, particularly SAP. We evaluate both of these in advance.

Why MaibornWolff?

As one of the most innovative IT service providers with a great passion for AI, we focus entirely on the project business and individual software development - without our own products. To stay at the forefront, we continuously invest in our team of digital technology engineers and develop digital solutions that are well thought-out, efficient and reduced to the essentials.

Our principle: simplicity instead of complexity. We only develop what is really needed - tailor-made, useful and reliable. Our results speak for themselves. With over 800 large-scale systems and more than 10,000 person-years of experience in high-end software engineering, we are one of the few who can reliably implement even the largest and most complex IT landscapes. Thanks to close partnerships with leading hyperscalers, our customers operate their solutions in today's most modern and powerful environments.

Less technology. Better Business.

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