Advice that comes from experience

We help you make the right decisions before you start building. That includes integration strategy, architecture selection, technical due diligence of your existing landscape, and an honest assessment of where custom development makes sense and where it does not. The outcome is a roadmap that works in practice, not just on slides.

Our consultants are experienced developers themselves and have built complex systems with their own hands. The advice you get from us is not theoretical. It comes from people who know what it takes to actually deliver and have learned the pitfalls over more than 30 years of project work.

Standard software fits when your processes are normal, an established product covers them well, and you need to move fast. Custom development pays off when it creates a real competitive advantage or when no product meets your specific requirements. In many cases the right answer is a combination: standard for the base, custom for the differentiation.

A quick assessment typically takes two to four weeks, a full digital strategy including architecture and roadmap usually six to twelve. We structure both formats around milestones with clear interim outputs, for example as-is analysis, architecture options, roadmap draft. That way you see solid initial findings after the first weeks instead of waiting for the final package. We work with workshops, stakeholder interviews and document analysis, and deliver a concrete recommendation at the end, not a generic strategy paper.

Yes. Our consulting does not end with a slide deck. The same team can carry the strategy through to delivery or work alongside your internal team and external partners. We can review architectures, guide vendor selection, or take on integration and development ourselves, whichever fits your project best.

We look at your workflows in concrete terms and identify where AI technology creates measurable value, in automation, personalisation or data analysis for example. We are equally honest about where AI does not make sense, or where data and process foundations need to be sorted out first. The outcome is a prioritised list of meaningful use cases, not an AI-at-any-cost plan.