Production AI · Built, deployed, operated

Built, shipped, still running.

We're the AI build team for enterprises that need the model to still be working eighteen months after the demo. Scope, build, operate — one team, no handoffs.

most stop
at shipped.
What we ship
Live engagements · 3 active
01
Workflow automation pipeline
Operations
Process automation + LLM orchestration
Operating
02
Adaptive education platform
EdTech
Multi-tenant adaptive learning
Build
03
AI capability workshop
Financial services · UAE
Executive workshop + capability roadmap
Delivered
// Engagement detail in What we ship · Full references under NDA on request
How we work

Three moves. One team. No handoffs.

01 · Scope

Scope

Two-week sprint to pressure-test the thesis, the data, and the appetite. We turn down work we can't ship. The Scope memo is a deliverable in itself — yours to keep, even if we don't proceed.

02 · Build

Build

Production-grade engineering. The same team that scoped it ships it. Evals, observability, governance and a cost envelope baked in from day one — not bolted on at the end.

03 · Operate

Operate

We stay. Drift, retraining, cost, latency, evals — the part that decides whether AI works a year from now, not just at the demo. Hand back to your team when they're ready, not when our retainer ends.

The thing we keep saying out loud

Pilots that survive have one thing in common: somebody actually built them.

— Michael Mudau, Managing Partner
Writing

What we publish.

Read all →
↗ start here
if you're new

Why 95% of AI pilots fail — and what the 5% have in common.

Six failure modes we've seen in the last eighteen months, and a working definition of "production-grade" that most consultancies refuse to commit to.

How we scope an engagement — and what we'll turn down.

Our actual scoping checklist, the projects we say no to, and why we publish our day rates instead of hiding them behind "let's talk."

the question we
keep getting asked

The handover question: when AI moves from project to product.

The transition that breaks most AI engagements — and the operating model we use to make it actually happen, not just appear on the closing slide.