We've worked with enough operators in Whanganui 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 data analytics project is sit with your team for a day before we propose anything.
For Whanganui operators who want a working pilot in weeks, not a year-long programme.
Our goal is to give Whanganui businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI data analytics actually does
Stop digging through dashboards. Ask plain-English questions of your sales, jobs, and customer data - get charts, summaries, and the why behind the numbers in seconds.
- 01 Natural-language queries over your Xero, Shopify, CRM data
- 02 Weekly auto-summaries delivered to inbox or Slack
- 03 Anomaly detection - flags weird weeks before you notice
- 04 Forecasts that explain themselves, not black boxes
Built on: DuckDB Claude Metabase BigQuery Vercel AI SDK
Without Kiwi Dynamics
With Kiwi 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 data analytics 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 Whanganui 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 data analytics compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi 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 |
Why Whanganui businesses are a fit for this.
- Whanganui blends creative scene, river-led tourism, and steady local trades - AI here helps small operators run lighter and reach further.
- Tourism, creative industries, and a growing remote-work population. AI tools that scale a small team's reach without enterprise overhead win.
We work with teams across Whanganui: Whanganui CBD · Castlecliff · Aramoho · Marton · Bulls.
Talk to us about this →
How we build AI data analytics for a Whanganui team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Whanganui business, so value lands before the build is finished. Ask your data in English.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Whanganui 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 Whanganui teams
The shape of the result for Whanganui teams: Owners check the business in 2 minutes instead of 2 hours. Built on DuckDB, 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 data analytics 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 Whanganui - so the savings start landing before the rest of the build is finished.
How do you price AI data analytics 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 Whanganui businesses are surprised how small the first cheque is.
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. Owners check the business in 2 minutes instead of 2 hours.
Will this run on our own infrastructure?
Yes, where it makes sense. AI data analytics can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK but the architecture supports your existing platform choices.
Worth a conversation?
Even if you don't end up working with us, you'll leave the call knowing what's worth building.
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.