The version of AI staff training 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 :)

There is a version of AI staff training 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.

What AI staff training actually does

Turn your senior team's brain into interactive training. AI-generated lessons, practice scenarios, and on-the-job coaching that scales without burning out your best people.

  • 01 Auto-generates training modules from your SOPs
  • 02 Voice-based roleplay scenarios for sales and service teams
  • 03 Tracks competency and flags refresher needs
  • 04 Works offline on site or in the truck

Built on: Claude ElevenLabs Vercel AI SDK Mux Postgres

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI staff training compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

Optometry practices run their businesses unlike anyone else.

  • 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.
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How we build AI staff training 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 training tools.

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How the work runs

The outcome for optometry practices

The shape of the result for optometry practices: New-hire ramp-up cut from 12 weeks to 5 - measurable competency, not just attendance. 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

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Kiwi Dynamics, that drops to about 52.

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*Based on 9 hours a week of admin at Kiwi Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

When does AI staff training actually pay back?

Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for an optometry practice - so the savings start landing before the rest of the build is finished.

How do you price AI staff training 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 optometry practices are surprised how small the first cheque is.

Has this actually shipped for a real optometry practice?

Yes. New-hire ramp-up cut from 12 weeks to 5 - measurable competency, not just attendance. We'll share comparable engagements on the call.

Will this run on our own infrastructure?

Yes, where it makes sense. AI staff training can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Claude, ElevenLabs, Vercel AI SDK, Mux, Postgres but the architecture supports your existing platform choices.

The honest version of a sales call.

No deck. No discovery doc. Just whether this is worth building and what it would cost.

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.