Built and supported here - the way a Geelong business would actually use it.

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

We've worked with enough operators in Geelong to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any AI fraud detection project is sit with your team for a day before we propose anything.

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

The Geelong context, plainly.

  • Geelong has rebuilt itself around health, education and advanced manufacturing since the car plants closed - AI here supports a city that's already proven it can reinvent.
  • A major hospital redevelopment, Deakin University's waterfront campus, and a manufacturing base that's shifted from cars to precision and renewables work. Geelong teams want AI that fits a city used to modernising fast.

We work with teams across Geelong: Geelong CBD · Newtown · Belmont · Corio · Ocean Grove · Torquay.

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How we build AI fraud detection for a Geelong team.

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

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How the work runs

The outcome for Geelong teams

What changes for Geelong teams after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. Recovers 3-5x its cost in caught fraud within 6 months.

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 long does AI fraud detection take to ship for Geelong businesses?

We aim for a working pilot inside 4-6 weeks - narrow scope, real Geelong businesses data, measurable outcome. From there it's another 6-8 weeks of hardening before you'd consider it production. Full rollouts (multiple sites, multiple teams) typically land in 3-4 months.

Are there hidden costs we should plan for?

Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.

Do you have proof this works for Geelong businesses?

Direct case study: Recovers 3-5x its cost in caught fraud within 6 months. Happy to walk you through full numbers on a call.

Who owns the code and the model setup?

You do, on delivery. We deploy AI fraud detection into your own cloud account where possible, with the model setup, prompts, evals and integration code all checked into a repo you own. Claude sits in your account too - we don't operate it from ours.

The honest version of a sales call.

No deck. No discovery doc. Just whether this is worth building and what it would cost.

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.