When a landscaping business 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.
Landscaping businesses · Applied AI
The version of AI demand forecasting that landscaping businesses still use a year after launch.
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 landscaping businesses reality
What we keep hearing from NZ landscaping businesses.
- Landscapers quote big jobs from a site visit and small jobs from a phone call, and both processes usually run on paper.
- Seasonal demand and slow quoting are the two things that most limit how much work a landscaping business can take on.
How we build AI demand forecasting for landscaping businesses.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a landscaping business business, so value lands before the build is finished. AI sales + stock forecasting.
Talk to usThe outcome for landscaping businesses
What changes for landscaping businesses after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. 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.
Questions
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 landscaping business – so the savings start landing before the rest of the build is finished.
Do you do hourly billing or fixed price?
Fixed price for the pilot, every time. After that it's your call – fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.
Do you have proof this works for landscaping 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.
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.