AI implementation for business

1. 01
   Free diagnostics

   30–90 minutes

   A maturity map, priorities ranked by money, a draft roadmap. Before any payment and before any data is shared. If the economics do not work at your scale, we say so here.

2. 02
   Secured perimeter

   week 1

   Corporate domain, single sign-on, access policy. An employee leaving means revoking everything in one action. Licences are issued to your company and stay yours.

3. 03
   The owner’s personal loop

   weeks 1–2

   We start with you, not the team. You personally get several times faster within the first two weeks — otherwise there is no reason for anyone else to believe the rest.

4. 04
   The anchor pilot

   weeks 2–5

   Trustworthy management accounting that answers in chat. Numbers are reconciled against the source and validated by your own accountant. This is the artifact that proves the system, not a demo.

5. 05
   Roles and automations

   weeks 4–8

   Each executive gets an AI staff office: the role is unpacked in a prompt interview, verified 5/5, and a triple of automations is driven to 100% with 7 days of verification.

6. 06
   The Keeper

   final

   Someone inside your team grows into the Keeper of the infrastructure — often the observer who sat in from day one. Their standing duty is the monthly context export into your own storage: playbooks, decision algorithms, prompts and memory layers as ordinary files, readable without us and without the vendor.

Pace: a team of 4–5 takes 6–10 weeks, roughly 15–20 joint sessions of 1–2.5 hours; a team of 2–3 takes 4–6 weeks. Training happens inside the sessions — daily solo work is 20–40 minutes per executive, so nobody steps away from operations.

What does implementation actually cost?

Diagnostics are free (30–90 minutes). Implementation starts at 3,900 USDT for 6–10 weeks, everything included — team training, the club and ongoing support. Payment comes in three tranches, 30 / 40 / 30, each tied to checklist acceptance of its stage. Licences for Claude and Google Workspace are billed by the vendors directly to your company: roughly $200–600 a month for a team of five.

How is this different from hiring an AI agency?

An agency delivers bots for isolated tasks. We rebuild how the company is managed: the executive team works inside one secured perimeter, every function becomes a project with accumulated context, and decisions are made on data the system can actually answer for. The bots most agencies sell become a by-product of that, not the point of it.

What happens to our data?

You remain the data controller; we act on your instruction. The anchor pilot runs on management aggregates and corporate records rather than personal data of individuals. Where personal data is genuinely needed, it is de-identified before it leaves your perimeter. If your policy does not allow cloud processing at all, we deploy a local model inside your network.

What if the team pushes back?

Each role is unpacked in a prompt interview and written into the system memory, so people see their own work described more precisely than they would describe it themselves. Work runs in triples — owner, employee, architect — on real company tasks. One automation is driven to 100% and verified for 7 days, and it is their automation. Headcount is cut only after the system works, never before.

What if we stop halfway?

You can. If an artifact is not accepted against its checklist, the next tranche is not invoiced. The corporate domain, single sign-on and configured access stay yours, and so does everything the Keeper has already exported into your own storage.

Who actually does the work?

Anton Ro Baten, management systems architect — 60+ growth projects before AI, $1.2B combined client turnover — with a technical lead and an implementation architect. Sessions are run by the people who designed the method, not by juniors.