We've worked with enough operators in Port Macquarie to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any AI demand forecasting project is sit with your team for a day before we propose anything.
AI sales + stock forecasting, built for businesses operating in Port Macquarie.
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
The Port Macquarie context, plainly.
- Port Macquarie is health, aged care and construction on the Mid North Coast, with an older population that still expects to reach a human on the phone.
- A retirement and health hub with a base hospital, a large aged-care sector and the trades building for constant inbound migration. Customer expectations skew toward phone and personal service, which is why voice AI has to be genuinely good here rather than a deflection.
We work with teams across Port Macquarie: Port Macquarie CBD · Wauchope · Lake Cathie · Thrumster · Settlement City.
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How we build AI demand forecasting for a Port Macquarie team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Port Macquarie business, so value lands before the build is finished. AI sales + stock forecasting.
Talk to usThe outcome for Port Macquarie teams
The shape of the result for Port Macquarie 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.
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 Port Macquarie - 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 Port Macquarie businesses are surprised how small the first cheque is.
Do you have proof this works for Port Macquarie businesses?
Direct case study: Stockouts down 35%, overstock down 22% in the first season. Happy to walk you through full numbers on a call.
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.
The honest version of a sales call.
No deck. No discovery doc. Just whether this is worth building and what it would cost.
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.