Working AI, built in front of your team.
John Arndt maps the work, red-lines what should change, and builds it live with the people who do it. Then he stays on as your accountable AI lead. Sometimes the note says leave it alone.

Four engagements. Each one bears on the next.
Start wherever your organization actually is. Every engagement stands alone, and every one leaves you with something working, written down, and owned by a named person on your side.
AI Readiness Assessment
“Where are we, honestly?”
Take the assessmentA self-scored survey of ownership, workflows, data and tools, people, and governance. It names your weakest dimension and the engagement that fits, including the case where the right move is to buy nothing yet.
About five minutes. Free. Runs in your browser; answers are not stored.
Live Build Workshop
“Can my team actually do this?”
Plan a workshopJohn and the people who do the work build one automation together, on approved examples of their real work, in one day. The team sees every decision, including what gets rejected and why.
One working day on site or remote, plus a short preparation call.
AI Build Sprint
“Get the important one into production.”
Scope a sprintA fixed-scope sprint that takes one to three workflows from mapped to operating in your environment. Options are tested on real examples before anything is installed, a named person reviews what needs judgment, and everything is documented for handoff.
Days to a few weeks, depending on the workflows. Scope and price agreed before work begins.
Fractional Chief AI Officer
“Who owns AI here, month after month?”
Discuss a fractional roleJohn joins your leadership rhythm as the accountable AI lead: setting priorities, deciding on tools and vendors, governing use, overseeing delivery, developing the team, and reporting what changed each month.
Monthly engagement. Scope and price agreed before work begins.

You work with the person holding the pencil.
Every engagement is led by John Arndt. He has more than a decade across AI, cybersecurity, fraud and risk, privacy, payments, and enterprise software, including roles at PayPal, Cloudflare, and Inscribe: fields where a wrong answer costs real money and a system has to be explainable to the person who signs for it. He now builds and operates AI software of his own, in public.
| Product | What it does |
|---|---|
| MentionedOn | Tracks how AI assistants describe and recommend local businesses. |
| Intakra | Turns public buying signals into a reviewed why-now brief for sales teams. |
| Dokyumi | Extracts structured data from business documents, with review before it lands. |
General notes. They apply to every sheet.
Build it on the real work
A demo on clean sample data proves nothing. Every option is tested on approved examples of your actual work before anything is installed.
Some work should stay manual
Rare cases, judgment calls, and anything where a mistake costs more than the time saved. Marking those early is part of the job, not a failure to sell.
A named person signs off
Where output reaches a customer, a record, or a decision, someone accountable reviews it. The review path is designed first, not bolted on after.
Your team can run it without me
Operating notes, access, and an internal owner are deliverables. If the system only works while I am in the room, it is not finished.
Not ready for a call? Survey the site first.
Fifteen questions across five dimensions. You get a readiness stage, your weakest dimension with the first move to fix it, and the engagement that fits. The rule behind the recommendation is printed with the result, so you can disagree with it.
| Ref | Dimension | What it checks |
|---|---|---|
| A | Ownership | Whether a named person is accountable for AI decisions and has the authority to make them. |
| B | Workflows | Whether the work is understood well enough to know what is worth changing. |
| C | Data & tools | Whether the information and approved tools exist for a system to do useful work safely. |
| D | People | Whether the team can use, question, and maintain what gets built. |
| E | Governance | Whether review, risk, and measurement are decided before something goes wrong. |
Reference sheets.
AI implementation
How a single workflow goes from mapped to operating, with the evaluation and handoff detail behind the Build Sprint.
AI training
Role-specific, hands-on programs for leaders and teams, beyond the one-day workshop.
Government & public sector
A distinct practice, scoped around agency authority, procurement, and public accountability.
Bring the workflow that slows you down.
Thirty minutes with John. You describe the bottleneck; he tells you what he would mark up, what he would leave alone, and whether Soxoa is the right fit.