When a building company asks us about AI demand forecasting, the first question we put back is the same one every time: which part of your week, if it disappeared, would change how you feel on a Friday? We start the build from that answer.
Building companies · Applied AI
AI demand forecasting that fits a building company's week, not the other way around.
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
The building companies reality
What we keep hearing from NZ building companies.
- Builders run multiple sites at once, and the paperwork behind each one grows faster than anyone has time to manage.
- Variations, supplier orders, and client updates are the admin layer that determines whether a build stays on schedule.
How we build AI demand forecasting for building companies.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a building company business, so value lands before the build is finished. AI sales + stock forecasting.
Talk to usThe outcome for building companies
Stockouts down 35%, overstock down 22% in the first season. For building companies, 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
What's a typical engagement length for building companies?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
Are there hidden costs we should plan for?
Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.
What's the realistic outcome for building companies?
Stockouts down 35%, overstock down 22% in the first season. We don't promise tenfold lifts because we don't see them outside of marketing decks.
Can you work with our existing systems?
Yes. The default AI demand forecasting stack we reach for is Prophet, DuckDB, Claude, BigQuery, Vercel, but we'll bend it around whatever you already run – Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
The honest version of a sales call.
No deck. No discovery doc. Just whether this is worth building and what it would cost.
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.