AI demand forecasting in Tauranga.
AI demand forecasting designed around the way a Tauranga team actually runs.
What this is
AI sales + stock forecasting
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.
Stockouts down 35%, overstock down 22% in the first season.
How it helps your Tauranga team
What you actually get.
- 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
Tauranga businesses don't need another generic AI pitch. AI demand forecasting only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in Bay of Plenty.
What changes for Tauranga teams after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. Stockouts down 35%, overstock down 22% in the first season.
Our field notes from Tauranga builds.
Horticulture, marine, logistics through the Port of Tauranga, and a booming services scene. Local businesses want AI that scales with seasonal swing.
We work with teams in
What we build
AI demand forecasting, tailored to Tauranga businesses.
- 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
Common questions
Before you book the call.
How quickly can we see something running? +
Week three for a clickable internal demo against real data. Week six for a slice your team can actually use. We hold ourselves to those numbers because they're what stops a project drifting into "endless discovery".
What's the smallest engagement you'd take on? +
A two-week paid discovery for Tauranga businesses 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.
Anyone else in this space using AI demand forecasting? +
Plenty. Stockouts down 35%, overstock down 22% in the first season. The interesting question is rarely "does it work" – it's "is your team ready to use the output." That's what we'd scope on the call.
What tools do you build AI demand forecasting on? +
For AI demand forecasting we usually reach for Prophet, DuckDB, Claude, BigQuery, Vercel. We're tool-agnostic at heart – we pick what your Tauranga team can actually run after we hand the build over, not what looks good on a vendor sticker.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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