E IS FOR ENGINEERING
Explore the passion behind engineering!
This is the story of how we designed our own locomotive.
"If a German engineer goes into the jungle with a few tin cans, he'll come out with a locomotive."
(Felix Wankel, German Engineer)
When we started improving business processes and workflows in the 1970s, we felt like the German inventor Felix Wankel described. Our tin can contained one of the oldest AI methods in existence: mathematical optimization. The jungle we entered was a corporate landscape that barely recognized the potential of business process optimization.
So, we designed our own locomotive: software that applied mathematical optimization methods to economic purposes for the first time. Our goal was to prove that companies could save money this way. And we succeeded! Mathematical optimization is the best method for planning production processes, transport sequences, procurement, or sales planning. It enables us to translate complex processes into mathematical models and calculate optimal process flows in seconds while considering all restrictions and a specified target.
This is why mathematical optimization remains at the core of our IT systems to this day. However, as engineers, we are constantly modifying the drive of our locomotive because we still have a few cans in stock. These cans contain the latest AI methods: process mining, machine learning, and generative AI. Driven by our pioneering spirit and engineering expertise, we will also leverage these methods to optimize operational processes.
We have transformed our locomotive into a high-speed train over the last 55 years.
E IS ALSO FOR
Expertise
The unique strength of our systems stems from the way we develop software. For us, it's about more than just the correct sequence of zeros and ones. Above all, our IT systems are built by listening, asking questions and understanding. After all, they must reflect the complexities of the real-world workplace. It’s not the code that makes the software; it’s our deep understanding of the specific challenges our customers face.
E IS ALSO ETHICS
At INFORM, artificial intelligence is a prerequisite, not an add-on. Wherever systems prepare or make decisions automatically, the same question always arises: Are the results transparent, accountable, and in the best interests of those affected? This is precisely where our understanding of AI ethics comes into play.
We develop AI systems that support decision-making rather than replace it. Humans are involved at all times and retain control ("human-in-the-loop"). We also ensure that the results are verifiable and adaptable, especially when decisions directly impact people. This is our approach to explainable AI.
Another key point is how we handle data. Transparency, data protection, and security are not secondary requirements but an integral part of system development.
For INFORM, AI ethics means taking responsibility for how AI is applied. We don't implement everything that is technically possible; only what is sensible, transparent, and accountable in real-world processes is implemented.
