Generative AI isn’t an end in itself. It’s a tool that takes work off your shoulders, improves products and supports your processes. But only if it’s used thoughtfully and embedded well. That’s where we come in. Not as outsiders, but as collaborators. From the first idea and prototype to full integration with your systems and products.
Generative AI is a new field full of question marks. There’s no single right solution, and not every use case is clear from the start. That’s why we move in small, clear steps. From the first overview to hands-on prototypes and finally full integration into your product and system landscape. Want to make your team work more efficiently with GenAI? Optimise customer service? Automatically modernise legacy code? Or talk to machine data? A lot is possible. And together we’ll figure out what really makes sense for you.
Step 1 | Create orientation
The first step is often the most important one. In a workshop we explore your current situation, challenge ideas and develop a first picture of where AI could really make a difference. And where it can’t. The result is a solid decision making base and a clear roadmap for the next steps.
Step 2 | Show what works fast
Theory alone won’t get you anywhere. We build prototypes or MVPs that show how AI can work in your context. These can be small but powerful tools. An internal chatbot. A smart analytics assistant. A feature that makes your product smarter. That way you can collect early feedback and decide whether a bigger rollout makes sense.
Step 3 | Substance over gimmicks
If a use case delivers, we turn it into a solid and scalable system. We integrate AI into your existing product and process landscape. Aligned with your architecture, data, security and governance. That way AI becomes part of your product strategy. Not a disconnected extra.
GenAI is not a standalone discipline. It only makes sense when connected to your entire product and system landscape. That’s exactly what we do:
GenAI should always be a means to an end. It only becomes relevant when it improves real products, takes pressure off teams and helps organisations move forward in a sustainable way. Our goal is to use AI in ways that create real value. Long term and with responsibility.”
Joachim Wilharm
Managing Director at slashwhy
A good prototype is often worth more than a hundred slides. That’s why we focus on fast, hands-on experiments that show early on how GenAI works in everyday use. This not only lets us test ideas more quickly, but also validate them directly with user feedback. An important step before investing in larger developments.”
Tobias Busch
AI Engineer at slashwhy
Many companies are facing the same challenge. AI tools are entering development teams. But clear structures, responsibilities and decision frameworks are missing. Between experimentation and uncertainty, between efficiency and quality, there’s a need for orientation.
That’s what this paper is here for. To support leaders who want to actively shape the AI shift. Not just react to it.