Engineers who got tired
of watching projects die slowly.
AIzexis started because every one of us, in our last job at a Fortune 500 or a name-brand agency, watched the same thing happen: a real problem walks in the door, gets staffed with juniors, gets stretched across quarters, gets billed in hours, and quietly dies. We left to do it differently.
What we believe
Skin > slides
If we can't share outcome risk, we shouldn't take your money.
Small > scaled
Ten seniors beat fifty mixed any day. We don't want to grow past it.
Code > calendar
Time-to-first-commit matters more than time-to-first-meeting.
Yours > ours
When we leave, your team can keep the system running without us.
The Executive team
Nazarii Kuspys
Sets technical direction across the team. Built and shipped large-scale ML systems at Meta before AIzexis.
Taras Rumezhak
Leads research engagements and computer-vision work. Oxford-trained; ran vision R&D at SoftServe.
Dmytro Lutchyn
Owns data infrastructure, MLOps, and production data pipelines. Came from data engineering at BMW.
Why we stay small.
Every consultancy that ever sold us a bad project started small and senior. They scaled by adding juniors and selling them as seniors. We've watched this movie. We're not making it.
The cap is ten. Always.