The version of AI demand forecasting that works for a Whanganui business is rarely the version a national vendor would sell you. We build the one that fits how your team actually operates – usually with fewer parts than the off-the-shelf pitch.
Manawatū-Whanganui · Applied AI
Built and supported here – the way a Whanganui business would actually use it.
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
Manawatū-Whanganui
The Whanganui context, plainly.
- Whanganui blends creative scene, river-led tourism, and steady local trades – AI here helps small operators run lighter and reach further.
- Tourism, creative industries, and a growing remote-work population. AI tools that scale a small team's reach without enterprise overhead win.
We work with teams across Whanganui: Whanganui CBD · Castlecliff · Aramoho · Marton · Bulls.
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How we build AI demand forecasting for a Whanganui team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Whanganui business, so value lands before the build is finished. AI sales + stock forecasting.
Talk to usThe outcome for Whanganui teams
The shape of the result for Whanganui teams: Stockouts down 35%, overstock down 22% in the first season. Built on Prophet, 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.
Questions
FAQ
When does AI demand forecasting actually pay back?
Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a Whanganui – so the savings start landing before the rest of the build is finished.
How do you price AI demand forecasting 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 Whanganui businesses are surprised how small the first cheque is.
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.
Will this run on our own infrastructure?
Yes, where it makes sense. AI demand forecasting can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Prophet, DuckDB, Claude, BigQuery, Vercel but the architecture supports your existing platform choices.
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.