Darwin 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 Darwin workflow, not bolted on the side.
Our goal is to give Darwin businesses a three-day weekend, so people can spend more time with their families and the people they love :)
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 you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI demand forecasting runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Darwin businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI demand forecasting compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Koala Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
The pattern across Darwin engagements we've shipped.
- Darwin runs on defence, resources and a tourism season split hard by the wet - AI here means handling seasonal swings without carrying seasonal headcount.
- A major defence presence, gas and resources projects, and a tourism trade that lives and dies by the dry season. Darwin businesses want AI that scales staffing-heavy work up and down without the overhead of actually hiring for it.
We work with teams across Darwin: Darwin CBD · Palmerston · Casuarina · Nightcliff · Parap · Stuart Park.
Talk to us about this →
How we build AI demand forecasting for a Darwin team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Darwin business, so value lands before the build is finished. AI sales + stock forecasting.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Darwin businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Darwin teams
If we build the right slice first, Darwin teams feel the difference inside the first month. Stockouts down 35%, overstock down 22% in the first season.
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
What's the realistic timeline for AI demand forecasting with a Darwin?
Most Darwin businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational - your team gets to use the thing well before the engagement is "done".
What does AI demand forecasting cost for a Darwin?
Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.
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.
What happens if we want to swap a vendor out later?
AI demand forecasting is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Prophet, DuckDB, Claude, BigQuery, Vercel are our defaults, but the build is intentionally portable.
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.