Most optometry practices we talk to aren't short of dashboards or tools - they're short of an hour back in the week. That's the lens we put on AI personalisation: not a tech showcase, but a careful look at the one or two workflows where an optometry practice is paying for the same problem to be solved twice.
Built for the optometry practice who's already tried the off-the-shelf option and bounced off it.
Our goal is to give optometry practices a three-day weekend, so people can spend more time with their families and the people they love :)
What AI personalisation actually does
Every customer sees the right product, message, and offer - based on what they've bought, browsed, and asked. Built on first-party data, no creepy tracking required.
- 01 Per-customer recommendations across web and email
- 02 Dynamic landing pages tailored to traffic source
- 03 Lifecycle messaging triggered by real behaviour
- 04 GDPR + NZ Privacy Act compliant by default
Built on: Claude Vercel Edge Postgres Klaviyo
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI personalisation runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for optometry practices first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI personalisation compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
Where optometry practices actually lose hours and dollars.
- 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 personalisation for optometry practices.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for an optometry practice business, so value lands before the build is finished. AI personalised CX.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing optometry practices the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for optometry practices
The shape of the result for optometry practices: Conversion lift of 18-32% over generic site experiences. 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
FAQ
What's the realistic timeline for AI personalisation with an optometry practice?
Most optometry practices have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".
What does AI personalisation cost for an optometry practice?
Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.
Do you have proof this works for optometry practices?
Direct case study: Conversion lift of 18-32% over generic site experiences. Happy to walk you through full numbers on a call.
What happens if we want to swap a vendor out later?
AI personalisation is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Claude, Vercel Edge, Postgres, Klaviyo are our defaults, but the build is intentionally portable.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
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.