About us
To our clients
Why most AI automation fails
Most AI automation we're asked to review does something impressive in a demo and nothing measurable in production. It breaks on the first input nobody thought of, and there is no one left who knows how to fix it.
What you get before we write code
You get a written scope first: what we'll build, what it should change, and what it will cost. If we think automation is the wrong answer to your problem, we'll say so — that conversation costs you nothing, and it has talked us out of work we could have billed for.
25 years of ERP and SAP implementation taught us where these projects actually fail. Rarely in the technology. Usually in scope that quietly drifts, systems nobody was trained to run, and a handover that never happens. That experience came from enterprise programs — Bombardier, Magna, Bell, SaskTel, ArcelorMittal — delivered across manufacturing, telecommunications, logistics, healthcare, utilities, retail, and professional services, before DesignareLux existed.
So we build small and hand it over. You own the system, your team knows how to run it without us, and nothing breaks if you stop returning our calls.
If that's the kind of engagement you want, let's talk.
Serguei Tyrtychnikov, PMP, PhD
Founder
We scope against two numbers: what it adds to revenue, and what it takes off cost.
A system your team can explain is a system that survives.