Dunedin businesses don't need another generic AI pitch. AI data analytics 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 Otago.
Ask your data in English - wired into a Dunedin workflow, not bolted on the side.
Our goal is to give Dunedin 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 Dunedin 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 |
What we keep seeing in Dunedin.
- Dunedin pairs a strong university research culture with practical southern businesses. AI here means proven tools, not hype.
- Education, health, tech, and a tourism shoulder season that hits hard. AI helps Dunedin teams smooth the peaks and protect the people.
We work with teams across Dunedin: CBD · North Dunedin · South Dunedin · Mosgiel · Port Chalmers · Green Island.
Talk to us about this →
How we build AI data analytics for a Dunedin team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Dunedin 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 Dunedin 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 Dunedin teams
If we build the right slice first, Dunedin teams feel the difference inside the first month. Owners check the business in 2 minutes instead of 2 hours.
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
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".
What's the smallest engagement you'd take on?
A two-week paid discovery for Dunedin businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Anyone else in this space using AI data analytics?
Plenty. Owners check the business in 2 minutes instead of 2 hours. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the call.
What tools do you build AI data analytics on?
For AI data analytics we usually reach for DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK. We're tool-agnostic at heart - we pick what your Dunedin 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.