AI fraud + anomaly, built for businesses operating in New Plymouth.

Our goal is to give New Plymouth businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Most of our New Plymouth engagements start the same way: a 20-minute call where the owner describes a workflow we've heard before in shape but never in detail. AI fraud detection is then designed against the detail, not the shape.

What AI fraud detection actually does

Pattern-watching AI for refund abuse, chargebacks, fake reviews, employee fiddles, and odd supplier invoices. Flags weirdness early - before it's a real problem.

  • 01 Learns your normal patterns and flags outliers
  • 02 Daily anomaly report, not a constant alert flood
  • 03 Explainable scoring so you can act with confidence
  • 04 Integrates with Xero, Shopify, and POS systems

Built on: Claude DuckDB Postgres Vercel

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI fraud detection compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

Why New Plymouth businesses are a fit for this.

  • Taranaki runs on energy, dairy, and engineering - industries with sharp safety, compliance, and uptime stakes that suit AI well.
  • From offshore work to dairy processors to a strong local trades sector, New Plymouth teams want AI that earns its keep on the gnarly stuff.

We work with teams across New Plymouth: CBD · Bell Block · Waitara · Inglewood · Oakura · Hawera.

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How we build AI fraud detection for a New Plymouth team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your New Plymouth business, so value lands before the build is finished. AI fraud + anomaly.

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How the work runs

The outcome for New Plymouth teams

The shape of the result for New Plymouth teams: Recovers 3-5x its cost in caught fraud within 6 months. Built on Claude, hardened with the rest of the stack as it scales.

Not your typical AI agency.

Honest about what AI can and cannot do

Ships the one workflow that pays for itself

Hours given back, never the size of the invoice

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Kiwi Dynamics, that drops to about 52.

Try the calculator

*Based on 9 hours a week of admin at Kiwi Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

When does AI fraud detection actually pay back?

Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a New Plymouth - so the savings start landing before the rest of the build is finished.

Do you do hourly billing or fixed price?

Fixed price for the pilot, every time. After that it's your call - fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.

Can you walk us through a comparable build?

Yes - on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Recovers 3-5x its cost in caught fraud within 6 months.

Will this run on our own infrastructure?

Yes, where it makes sense. AI fraud detection can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Claude, DuckDB, Postgres, Vercel but the architecture supports your existing platform choices.

Skip the pitch.

Tell us the workflow and we'll come back with what we'd build first.

Talk to us about this

Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.