AI fraud detection that lives in your stack, not on a vendor's roadmap. Shipped from Queensland.

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

Brisbane sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI fraud detection template would catch.

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 toolKoala 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

What we keep seeing in Brisbane.

  • Brisbane is in the middle of an infrastructure and population boom running through to the 2032 Olympics - AI here is about keeping growing businesses from drowning in their own admin.
  • Construction, property and a fast-growing professional services base are all hiring faster than they can train people. Brisbane teams need automation that lets a smaller back office keep pace with a bigger front line.

We work with teams across Brisbane: CBD · Fortitude Valley · South Bank · Chermside · Ipswich · Springfield.

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How we build AI fraud detection for a Brisbane team.

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

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How the work runs

The outcome for Brisbane teams

The shape of the result for Brisbane 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 Koala Dynamics, that drops to about 52.

Try the calculator

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

FAQ

How fast could we have AI fraud detection in production?

Eight to ten weeks for most Brisbane businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.

What's the smallest engagement you'd take on?

A two-week paid discovery for Brisbane businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.

What's the realistic outcome for Brisbane businesses?

Recovers 3-5x its cost in caught fraud within 6 months. We don't promise tenfold lifts because we don't see them outside of marketing decks.

What if our Brisbane doesn't have any data ready?

Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI fraud detection specifically, we typically run that work on Claude, DuckDB, Postgres, Vercel and assume messy starting conditions from day one.

Sketch this with us.

We'll map your real workflow before quoting anything.

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.