We don't deploy AI. We design how decisions get made.
The data layer is one of three pillars of an AI-native company. Here's what that looks like, and how we build it for SMEs in 90 days.
Most consultancies sell you tools. We build a connected layer with three load-bearing parts.
What a closed loop actually looks like.
01
Data — what happened.
02
Context — why it matters for the business.
03
Interpretation — what it means.
04
Decision — what we do.
05
Action — who does it, when.
06
Feedback — what changed because of it.
This is not a chatbot. Not a dashboard. Not automation. It is a way of operating.
Manual first. Habit next. Automation after.
Stage 0 · Diagnosis · 5 days. Before anything is built, we agree on the workflow, the owner, the one question your system must answer in 14 days. The deliverable is a single page on A4. This is where most projects get killed by ambition. We keep it small.
Stage 1 · First Loop · 14 days. We build the smallest working loop end-to-end. One shared table, one source-of-truth map, a five-block dashboard, a five-document context pack, weekly AI interpretation, human approval, and an action tracker. Manual. No automation. By day 14, the first AI-recommended action has been approved and executed.
Stage 2 · Make it Stick · 14 days. The most underrated stage. We document the rhythm, fix the data gaps the first cycle exposed, improve the context pack, and add one automation — usually the weekly data pull. After four cycles, the loop is no longer a project. It's how the team works.
Stage 3 · Second Loop · 30 days. We prove the model is reproducible. Different workflow type, same infrastructure. And — for the first time — the loops connect: an insight from loop one creates a task in loop two. This is where two-way translation begins.
Stage 4 · Two-Way Translation · 21 days. Strategy now flows down through the same system data flows up through. Q3 objectives, brand voice, pricing rules, regional positioning, budget principles — all encoded as machine-readable logic. Approval workflows scale: small decisions auto-approve, medium fast-track, large get full review.
Stage 5 · Governance & Scale · Ongoing. Role-based access, audit trail, EU AI Act and GDPR baseline, documented transparency, human oversight. Then expansion: sales, finance, customer success, operations.
Where we deliberately stop.
We don't replace your marketing team with agents. We don't sell black-box automation that nobody on your team can audit. We don't add a vector database before you need one. We don't give AI raw access to your business systems. We don't build approval workflows that take three days. We don't bolt governance on at the end.
If a vendor is selling you any of the above, we'd rather you save the budget.