Kalgoorlie sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI demand forecasting template would catch.
AI sales + stock forecasting - wired into a Kalgoorlie workflow, not bolted on the side.
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 Koala Dynamics
With Koala Dynamics
What Kalgoorlie teams tell us when they get on a call.
- Kalgoorlie is gold - the Super Pit and a whole services economy around a fly-in workforce.
- Gold mining, mining services and a FIFO population that changes the customer base week to week. Rostering, callouts and after-hours contact are where the time actually goes.
We work with teams across Kalgoorlie: Kalgoorlie CBD · Boulder · South Kalgoorlie · Hannans · Coolgardie.
Talk to us about this →
How we build AI demand forecasting for a Kalgoorlie team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Kalgoorlie business, so value lands before the build is finished. AI sales + stock forecasting.
Talk to usThe outcome for Kalgoorlie teams
Stockouts down 35%, overstock down 22% in the first season. For Kalgoorlie teams, 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.
FAQ
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".
Is AI demand forecasting worth it for a smaller Kalgoorlie?
Often, yes - and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.
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 Kalgoorlie team can actually run after we hand the build over, not what looks good on a vendor sticker.
One short call.
Tell us what you're trying to fix. We'll come back inside a working day.
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.