AI fraud detection in Ashburton.
AI fraud detection that lives in your stack, not on a vendor's roadmap. Shipped from Canterbury.
What this is
AI fraud + anomaly
Pattern-watching AI for refund abuse, chargebacks, fake reviews, employee fiddles, and odd supplier invoices. Flags weirdness early – before it's a real problem.
Recovers 3-5x its cost in caught fraud within 6 months.
How it helps your Ashburton team
What you actually get.
- Learns your normal patterns and flags outliers
- Daily anomaly report, not a constant alert flood
- Explainable scoring so you can act with confidence
- Integrates with Xero, Shopify, and POS systems
The reason we take on work in Ashburton is that the businesses here tend to be sharper about what they want than the brief lets on. AI fraud detection for a Ashburton team almost always ends up looking different to AI fraud detection for a downtown Auckland one.
The shape of the result for Ashburton 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.
What we keep seeing in Ashburton.
Dairy, arable, and a strong engineering base supporting irrigation and processing. AI lands well when it makes long days shorter.
We work with teams in
What we build
AI fraud detection, tailored to Ashburton businesses.
- 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
Common questions
Before you book the call.
How fast could we have AI fraud detection in production? +
Eight to ten weeks for most Ashburton 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 Ashburton 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.
Do you have proof this works for Ashburton 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.
What if our Ashburton 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.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
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