When an optometry practice asks us about AI recruiting, the first question we put back is the same one every time: which part of your week, if it disappeared, would change how you feel on a Friday? We start the build from that answer.
The version of AI recruiting that optometry practices still use a year after launch.
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 recruiting actually does
Job ads written for SEEK, Trade Me, and LinkedIn. CVs screened against role criteria with reasoning. Phone screens done by voice AI - so shortlists land on your desk ready to interview.
- 01 Drafts compliant NZ job ads with realistic salary bands
- 02 Screens CVs and ranks by fit with written rationale
- 03 Voice AI runs first-round phone screens 24/7
- 04 Bias checks built in - flagged in the audit log
Built on: Claude Vapi Workable SEEK API Vercel
Without Kiwi Dynamics
With Kiwi Dynamics
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 recruiting 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 recruiting 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 |
What years of building for optometry practices taught us.
- 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 recruiting 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 candidate screening.
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
We'd call the engagement a success when optometry practices are using the system without thinking about us. Time-to-shortlist drops from 3 weeks to 4 days.
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
How long does AI recruiting 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.
Do you have proof this works for optometry practices?
Direct case study: Time-to-shortlist drops from 3 weeks to 4 days. 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 recruiting 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.
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.