Riaan Kleynhans · AI enablement
I get AI out of pilots and into daily work
For regulated European enterprises: the work redesigned around the AI, the people brought along, and governance that lets it scale — with results you can measure.
For COOs, CDOs and heads of transformation whose AI is stuck in pilots.
Where is your AI stuck?
Three questions, an answer straight away
Runs in your browser — nothing is sent or stored.
Answer the three questions and your next step appears here.
Who this is for
For AI that exists — and hasn’t reached the work yet
A fit if
- You run AI pilots, and few or none of them are used in the daily work.
- You have a reason to move now: a board mandate, a budget round, an audit or the AI Act timeline.
- Your CISO, legal or compliance lead can say no — and you want them in the room from the start.
- You would rather stop a pilot than scale one that doesn’t pay.
Not a fit if
- You want a chatbot built quickly, or a licence to buy.
- You have no pilots yet. The three questions above will say so, and point you to where to start.
- You need a result promised before anyone has looked.
- Nobody on your side will put their name to a decision.
My first focus is financial services, where the AI Act and an auditor are already in the room. Outside it, the method is the same; the industry playbook is newer, and I’ll say so on the call.
What I do differently
Every step proven, not presented
Adoption, not pilots
Success is AI used in the daily work, measured by adoption and realised value — not by how many pilots were launched.
How I work →Proof built in
Every number comes from a rule or a source you can follow. What isn’t known is shown as unknown. Every decision is signed by its owner.
See how it’s checked →Built, not just advised
I have shipped what AI needs before people trust it to act: identity, memory and voice — my own products.
What I have built →The same rules for my own marketing
What I publish passes the checks I ask of clients: sourced figures, no buzzwords, no bait, one honest limit in every piece.
My rules →
Where the effort goes
The model is the smallest part of the work
An AI programme is mostly people and process. That is where pilots stall — and where I work.
- 10 % · AlgorithmsChoosing, prompting or tuning the model.
- 20 % · Technology and dataPipelines, integrations and the data the model needs.
- 70 % · People and processesRedesigned workflows, decision rights, training and adoption.
Source: Boston Consulting Group (BCG), the 10-20-70 principle.
How I work
Five phases, from diagnosis to adoption you can measure
Each phase ends in something signed, not a slide. The engine carries what can be computed; I bring the rest with your teams.
- 1Align and diagnose
Leadership agrees the value at stake; processes, the AI already in use and readiness are mapped on evidence.
Measured by: a signed value floor and a readiness baseline
The engine plus hands-on work
- 2Redesign the work
The workflow is rebuilt around the AI: who decides, where a human reviews, how the team is sized.
Measured by: decision rights signed by their owners
The engine plus hands-on work
- 3Prove it in a governed pilot
One high-value workflow, with EU AI Act classification, evidence and an audit trail built in.
Measured by: cycle time and value against the floor
The engine plus hands-on work
- 4Bring people along
Role-based learning, a champions network and team libraries of prompts and agents — so the new way of working is the one people use.
Measured by: adoption per workflow
Hands-on with your teams
- 5Scale what works
Wins become standard modules with owners, an operating rhythm and a value ledger.
Measured by: realised value, not seat licences
The engine plus hands-on work
Phase 4 is delivered hands-on today; the engine’s support for it — cohorts, champions, adoption tracking — is being built.
Is it safe?
Safe to scale, because it is checked
- Every decision is signed by the person who owns it.
- Every AI use case is risk-classified before it goes live.
- Every number can be traced to where it came from — what isn’t known is shown as unknown.
923 automated checks passed on 2026-10-06. · See how it’s built
Questions you’re probably asking
Straight answers
- What do you do differently?
- I get AI out of pilots and into daily work. Every step is proven rather than presented: numbers from rules or sources, decisions signed by their owners, unknowns shown as unknown.
- Is this another AI tool?
- No. It’s a way of getting the AI you already have into daily work. The software you see here makes the method visible; you don’t buy a licence.
- How quickly will we see something?
- The Scan takes 3 weeks. At the end you know where you stand and which use case deserves a pilot.
- What does it cost to start?
- The Scan costs €15,000–€25,000, set by the scope and fixed once quoted. After it, you decide whether to go further.
- Do we need clean data or new software first?
- No. We start with the tools and data you have. Where the data isn’t ready, that becomes a gap with an owner and a date — not a reason to wait.
- What about the EU AI Act?
- Every use case is classified before it goes live, and the record is ready for your counsel. It isn’t legal advice — your lawyers decide.
- Who does the work?
- I do, with your teams. Most phases are supported by the engine; bringing people along is hands-on work.
Start here
Start with the Scan
€15,000–€25,000, fixed once scoped, 3 weeks — and you know which pilot is worth taking live, and what it is worth.