We take AI into production.
And keep it there.
Four rules we don’t bend.
We're engineers first. We've seen what happens when AI projects get big, fuzzy and reversible-only-in-theory. These rules are how we avoid becoming one.
Ship · then measure
We do not build "PoCs". Every engagement ships to prod with SLOs, rollbacks and monitoring on day one.
Reversible by default
Every agent we put in the loop has a kill-switch, a manual override, and an audit trail. Nothing goes one-way.
Own the boring layer
Eval harnesses, data pipelines, observability. The unglamorous work that decides whether AI survives contact with reality.
No model-worship
We use the smallest model that clears the bar. Frontier weights are an option, not a brand.
Small on purpose. Senior everywhere.
Sean D.
Builds AI systems for payments, fraud prevention and financial intelligence. Sets product direction; ships first.
Ilya N.
End-to-end full-stack on AI-powered fintech. Ships from data layer to UI without handoffs.
Kirill K.
Analytics in HEX over ClickHouse. Turns events into answers, not dashboards.
Alex E.
Stands up infra across Kubernetes, AWS and Yandex Cloud. Multi-cloud by default, vendor-locked nowhere.
Alexey S.
Architecture for agentic systems. Owns the load-bearing layer end-to-end.
Andrey S.
Publishes on AI engineering and runs the RAG track. Bridges paper and prod.
Two years. No pivots.
Sean + Ilya — two paths, one goal.
FraudShield v1 — 6 weeks from kickoff to production.
Finance first — then retail, legal, logistics, insurance, healthcare, public sector.
6 engineers. Still shipping.
What two years looks like.
Work here.
We hire seniors. No bootcamps, no ramp-up sandbox — you land on a real integration in week 1, with a principal shipping alongside you. Remote-first, quarterly in-person weeks in Lisbon.