AI demand forecasting for optometrists.
For optometry practices who want results in weeks, not a year-long transformation programme.
How the work runs
We find the one workflow costing optometry practices the most hours, ship a working slice into production in weeks, prove it pays for itself, then harden it and hand it over.
Eye test recalls, bookings and patient messages handled automatically, with patient information protected under the Privacy Act 2020.
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.
What AI demand forecasting actually does
Forecasts that account for school holidays, NZ weather, tourist seasons, and your own promo calendar. With the right workflow automated, nine hours of admin a week could drop to about one.*
*Illustrative example only, based on 9 hours a week of admin falling to about 1 hour a week. Actual results vary by workflow and business.
An AI agency, minus the theatre.
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Less admin.
More weekend.
No theatre.
What you get
Stockouts down 35%, overstock down 22% in the first season.
- Combines your sales history with weather, calendar, and event data
- Per-SKU and per-store forecasts, not whole-business averages
- Re-forecasts weekly as new data comes in
- Explains the why behind every number
- No annual contracts
- No shelfware or licences you do not use
On the tools or running at scale, the admin still eats the week :)
The questions a public sector buyer asks, answered up front: privacy impact, the NZISM, where the data lives and how an algorithm is held to account.
*Illustrative example based on nine hours a week of admin. Actual results vary by workflow and business.
Straight answers
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.
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.
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.
Can you work to the NZISM?
The NZISM is the government's information security manual and is written for vendors serving agencies as well as the agencies themselves, so government-adjacent work should be built to it.
Does scheduling handle public holidays?
It should. New Zealand has 11 national public holidays, including Matariki, plus a regional anniversary day that depends on where your business is.
Let's chat
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