Every optometry practice business we've worked with has a different definition of "broken". AI demand forecasting only earns its keep when it solves the specific definition you'd give it on a bad day – which is why our first call is mostly listening.
Optometry practices · Applied AI
For optometry practices who want results in weeks, not a year-long transformation programme.
What AI demand forecasting actually does
Forecasts that account for school holidays, NZ weather, tourist seasons, and your own promo calendar. Order the right stock, roster the right hours, plan the next quarter with actual numbers.
- 01 Combines your sales history with weather, calendar, and event data
- 02 Per-SKU and per-store forecasts, not whole-business averages
- 03 Re-forecasts weekly as new data comes in
- 04 Explains the why behind every number
Built on: Prophet DuckDB Claude BigQuery Vercel
Without Kiwi Dynamics
With Kiwi Dynamics
Lay of the land
The two or three things that decide whether this works for 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 demand forecasting 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 sales + stock forecasting.
Talk to usThe outcome for optometry practices
Stockouts down 35%, overstock down 22% in the first season. For optometry practices, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.
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 fast could we have AI demand forecasting in production?
Eight to ten weeks for most optometry practices. 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 optometry practices 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.
Can you walk us through a comparable build?
Yes – on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Stockouts down 35%, overstock down 22% in the first season.
What if our optometry practice 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 demand forecasting specifically, we typically run that work on Prophet, DuckDB, Claude, BigQuery, Vercel and assume messy starting conditions from day one.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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.