Consulting that
delivers through execution

Here Are Some of Our Cases:

• Case 1. A large logistics company faced annual software licensing costs of tens of millions of euros, the licenses were tracked inefficiently, and overpayment was common. The IT team had spent 1.5 years developing an internal system to fix this, but they constantly needed to beg for financing the effort, as the business unit saw it only as inefficient costs.
• Case 2. A promising consumer electronics startup found itself trapped between two centuries: their "Dutch guild" style production model (mentorship and minimal automation) was hitting its limits. To grow productivity would require dismantling the organizational structure that got them this far.
• Case 3. A drone inspection company seemed to have everything: innovations, services, expertise. It was trying to do everything: power line inspections, 3D mapping, flights all over Europe, manufacturing their own drones. But they lacked strategic vision of what they were about, nothing was done well enough, and their main client, a major German electric grid operator with 50,000+ km of power lines, was constantly dissatisfied.

Here is How They Turned Out:

• Case 1, the logistics company. The internal license-auditing system evolved into a cross-departmental tool integrated with procurement, HR, and security systems. This reduced manual reconciliation work by 8,000 hours/year and cut licensing overpayments by €5.2M annually. making the solution self-funded and a cornerstone of the company's IT infrastructure.
• Case 2, the consumer electronics startup. Transitioning to a divided workflow system, with automated QA checks, tripled productivity (reduced average device assembly time from 14.2 to 4.8 hours: -66%). The startup achieved €287K quarterly savings, and was positioned for scalable growth and potential "unicorn" status in its niche.
• Case 3, the drone inspection company. The "digital twin" implementation for the main client, a grid operator consolidated asset conditions (2.1M inspection data points), financial planning models, and maintenance protocols. This enabled predictive replacement of 423 transformers before failures occurred (vs. 112/year previously), saving the client €1.9M in emergency repairs. The company shifted 73% of staff from manual reporting to AI-assisted analysis.

You can read these cases and others like them in the carousel below.