AI does not fix problems. It amplifies them.
We spent 14 years fixing enterprise data, processes, and governance for companies like Metro AG, Lagardère, and a Fortune 500 US company in Financial Services and Insurance. That's why our AI works in production — not in pilots.
Everyone asks. Here's our answer: start with the phase you're actually in. Most organizations think they're ready to deploy. Most are actually one or two phases earlier — and finding that out now costs a fraction of finding it out after the budget is spent.
10
5 weeks
+25 /-17%
10,000+
+14 yrs.
OUR CUSTOMERS
Trusted across the Metro and Lagardère ecosystems — and inside a Fortune 500 US company in Financial Services and Insurance.
Financial Services & Insurance
Travel Retail
Retail
Travel Retail
Wholesale & Distribution
Technology & IT Services
METRO ROMÂNIA
Wholesale & Distribution
METRO AUSTRIA
Wholesale & Distribution
Fourteen years of enterprise delivery — for three billion-dollar-plus enterprises, including a Fortune 500 US company in Financial Services and Insurance.
One firm. Two ways in.
01
Data & Analytics
Where we made our name. Data platforms, enterprise BI, complex migrations, and the engineering discipline that keeps mission-critical reporting alive seven days a week. If your foundations are the problem, start here.
02
AI
Where the foundations pay off. Readiness assessments that tell you the truth, production AI platforms built in weeks on fixed price, and the fluency programs that make your people dangerous with AI instead of dangerous to it.
They're not two businesses. Data is Phase 1 and 2 of every AI initiative that survives. That's the whole point.
Three things we've learned the expensive way — on other people's programs.
01
Architecture debt cannot be hidden forever.
Front-end compensation can delay collapse - not prevent it.
02
Decision velocity is a competitive advantage.
Where large delivery structures escalate for weeks, we decide in days. The performance delta isn't talent alone — it's speed of decision.
03
“Not possible” usually means “not attempted deeply enough.”
We have repeatedly engineered platform-level solutions that others declared unavailable.
We've replaced a Tier-1 global strategy consultancy. We've outdelivered offshore giants at a Fortune 500. Not by being bigger. By being better — and being able to prove it.
FLAGSHIP
Six people. Five weeks.
In production.
A custom enterprise Budgeting & Forecasting Platform for Lagardère Travel Retail — designed, built, validated against historical cycles, and deployed with Claude Code and Spec-Driven Development. Now through its first full budget cycle, recovering an estimated 1,100–1,330 finance-team hours per year.
From spreadsheets that lock up to a planning engine that scales.
Where do we start with AI?
Everyone asks. Here's our answer: start with the phase you're actually in. Most organizations think they're ready to deploy. Most are actually one or two phases earlier — and finding that out now costs a fraction of finding it out after the budget is spent.