AI demand forecasting in Kaikōura.
AI demand forecasting designed around the way a Kaikōura team actually runs.
Kaikōura welcomes around a million visitors a year. We automate bookings, enquiries and reviews so small teams keep up with big seasons.
Knows the New Zealand rules.
Demand and cash flow forecasts from your own history, including the harvest, school holiday and public holiday swings your business actually has.
- 11 public holidays, plus yours
- Four school terms a year
- The Public Service AI Framework
An AI agency, minus the theatre.
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Already buried in admin? We'll sort the first workflow for you :)
Nine hours a week of admin is 468 hours a year. That could drop to about 52.*
*Illustrative, based on 9 hours a week of admin at a typical 80% automation rate. The calculator uses your own numbers.
Kaikōura, up close.
Tourism, directly and indirectly, is the major contributor to Kaikōura's GDP, built on whales, the coastline and crayfish, alongside the district's fishing and farming heritage.
A deep undersea canyon brings Giant Sperm Whales close to the coast, and Whale Watch has run since 1987.
One workflow.
In production.
In weeks.
What you get
If we build the right slice first, Kaikōura teams feel the difference inside the first month.
- Combines your sales history with weather, calendar, and event data
- Per-SKU and per-store forecasts, not whole-business averages
- Re-forecasts weekly as new data comes in
- Explains the why behind every number
- No annual contracts
- No AI theatre
From one-person trades to national organisations, we find the hours :)
The questions a public sector buyer asks, answered up front: privacy impact, the NZISM, where the data lives and how an algorithm is held to account.
*Illustrative example based on nine hours a week of admin. Actual results vary by workflow and business.
Straight answers
What's the realistic timeline for AI demand forecasting with a Kaikōura?
Most Kaikōura 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 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.
Is AI demand forecasting worth it for a smaller Kaikōura?
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.
Can you work to the NZISM?
The NZISM is the government's information security manual and is written for vendors serving agencies as well as the agencies themselves, so government-adjacent work should be built to it.
What does the Privacy Commissioner expect before we use AI?
Senior leadership sign-off, a check that the tool is necessary and proportionate, and a privacy impact assessment before it goes live.
Talk to us about AI demand forecasting
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Tell us what you're trying to do and we'll reply with how we'd build it, no obligation.
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