The version of AI data analytics that works for a Kerikeri business is rarely the version a national vendor would sell you. We build the one that fits how your team actually operates – usually with fewer parts than the off-the-shelf pitch.
Northland · Applied AI
For Kerikeri operators who want a working pilot in weeks, not a year-long programme.
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
Northland
The Kerikeri context, plainly.
- Kerikeri is horticulture, tourism, and a fast-growing lifestyle community – AI here is about connecting orchard, paddock, and storefront.
- Kiwifruit, citrus, and a steady hospitality scene serving the Bay of Islands. AI tools that work in low-signal areas land best.
We work with teams across Kerikeri: Kerikeri central · Waipapa · Kaitāia · Russell · Paihia · Mangonui.
Talk to us about this →
How we build AI data analytics for a Kerikeri team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Kerikeri business, so value lands before the build is finished. Ask your data in English.
Talk to usThe outcome for Kerikeri teams
Owners check the business in 2 minutes instead of 2 hours. For Kerikeri 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Questions
FAQ
What's a typical engagement length for Kerikeri businesses?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
Are there hidden costs we should plan for?
Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.
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.
Can you work with our existing systems?
Yes. The default AI data analytics stack we reach for is DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK, but we'll bend it around whatever you already run – Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
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.