The version of AI efficiency audit that works for a Whakatāne 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.
For Whakatāne operators who want a working pilot in weeks, not a year-long programme.
Our goal is to give Whakatāne businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI efficiency audit actually does
A two-week audit that maps your team's actual time spend, finds the 5 highest-leverage AI plays, and ships the first one. No vapourware, no 80-slide decks - just one working thing.
- 01 Time-and-motion review of your top 5 workflows
- 02 Ranked AI opportunity list - ROI, effort, risk
- 03 One pilot shipped in week two, not a six-month roadmap
- 04 Fixed price, fixed scope, kept honest
Built on: Claude Notion Loom Linear Vercel
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 efficiency audit 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 Whakatāne 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 efficiency audit 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 |
The Whakatāne context, plainly.
- Eastern Bay of Plenty runs on horticulture, aquaculture, and Māori-led enterprise - AI here works when it respects relationships first.
- Kiwifruit, aquaculture, marine tourism, and a strong iwi economy. AI tools that work offline and bilingually find their home here.
We work with teams across Whakatāne: Whakatāne · Ōhope · Kawerau · Edgecumbe · Murupara · Ōpōtiki.
Talk to us about this →
How we build AI efficiency audit for a Whakatāne team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Whakatāne business, so value lands before the build is finished. Find AI wins fast.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Whakatāne 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 Whakatāne teams
The shape of the result for Whakatāne teams: Average pilot saves 8 hours/week within 30 days of launch. Built on Claude, 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 efficiency audit 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 Whakatāne - so the savings start landing before the rest of the build is finished.
How do you price AI efficiency audit 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 Whakatāne businesses are surprised how small the first cheque is.
Has this actually shipped for a real Whakatāne?
Yes. Average pilot saves 8 hours/week within 30 days of launch. We'll share comparable engagements on the call.
Will this run on our own infrastructure?
Yes, where it makes sense. AI efficiency audit can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Claude, Notion, Loom, Linear, 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.
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.