AI demand forecasting that lives in your stack, not on a vendor's roadmap. Shipped from Victoria.

Our goal is to give Melbourne businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Melbourne 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 Victoria.

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

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI demand forecasting compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKoala Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

Our field notes from Melbourne builds.

  • Melbourne's economy runs on education, healthcare, retail and a dense creative and hospitality sector - AI earns its keep here on volume and margin, not novelty.
  • Two of the country's biggest universities, a major hospital network, and a retail and hospitality scene that never really slows down. Melbourne teams are practical about tools that save real hours across rosters, bookings and back-office work.

We work with teams across Melbourne: CBD · Docklands · Richmond · St Kilda · Box Hill · Dandenong.

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How we build AI demand forecasting for a Melbourne team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Melbourne business, so value lands before the build is finished. AI sales + stock forecasting.

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How the work runs

The outcome for Melbourne teams

Stockouts down 35%, overstock down 22% in the first season. For Melbourne 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

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Koala Dynamics, that drops to about 52.

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*Based on 9 hours a week of admin at Koala Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

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 Melbourne?

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.

What's the realistic outcome for Melbourne businesses?

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.

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 Melbourne team can actually run after we hand the build over, not what looks good on a vendor sticker.

Twenty minutes, your call.

You describe what's broken. We'll tell you what we'd actually do about it.

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.