The version of AI fraud detection that works for a Katherine business is rarely the version a national vendor would sell you. We build the one that fits how your team actually operates - usually with fewer parts than the off-the-shelf pitch.
Built and supported here - the way a Katherine business would actually use it.
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
Without Koala Dynamics
With Koala Dynamics
Why Katherine businesses are a fit for this.
- Katherine is defence, pastoral country and transport where the Stuart and Victoria highways meet.
- RAAF Base Tindal, cattle stations, horticulture and freight. Defence work brings compliance requirements, and pastoral clients are often hours from the nearest town.
We work with teams across Katherine: Katherine CBD · Katherine East · Katherine South · Tindal · Mataranka.
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How we build AI fraud detection for a Katherine team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Katherine business, so value lands before the build is finished. AI fraud + anomaly.
Talk to usThe outcome for Katherine teams
If we build the right slice first, Katherine teams feel the difference inside the first month. 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
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 Katherine - so the savings start landing before the rest of the build is finished.
How do you price AI fraud detection engagements?
Fixed-scope pilots first, then either project pricing or a small monthly retainer for the ongoing work. No long lock-ins, no 18-month black-box deals. Most Katherine businesses are surprised how small the first cheque is.
Do you have proof this works for Katherine 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.
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.