There is a version of AI fraud detection that optometry practices buy off a shelf and quietly stop using inside a month. Then there's the version that's wired into your real workflow, owned by a person on your team, and still in use a year later. We only build the second one.
Optometry practices · Applied AI
AI fraud detection that fits a optometry practice's week, not the other way around.
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 Kiwi Dynamics
With Kiwi Dynamics
The optometry practices reality
What we keep hearing from NZ optometry practices.
- Optometrists balance eye tests, recalls, and frame sales, with recall reminders often the first thing to slip.
- Recall reminders and insurance or funding queries are the recurring admin load behind every optometry front desk.
How we build AI fraud detection for optometry practices.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a optometry practice business, so value lands before the build is finished. AI fraud + anomaly.
Talk to usThe outcome for optometry practices
If we build the right slice first, optometry practices 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.
Questions
FAQ
How long does AI fraud detection take to ship for optometry practices?
We aim for a working pilot inside 4-6 weeks – narrow scope, real optometry practices 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.
Has this actually shipped for a real optometry practice?
Yes. Recovers 3-5x its cost in caught fraud within 6 months. We'll share comparable engagements on the 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.
Skip the pitch.
Tell us the workflow and we'll come back with what we'd build first.
Get in touch
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.