Auto repair shops are some of the most efficient operators in New Zealand - which means the easy wins from AI compliance monitoring are usually already taken. The brief we accept is the one focused on the workflow you've tried to fix twice and given up on.
Built for the auto repair shop who's already tried the off-the-shelf option and bounced off it.
Our goal is to give auto repair shops a three-day weekend, so people can spend more time with their families and the people they love :)
What AI compliance monitoring actually does
AI that watches your forms, calls, contracts, and emails for compliance risk - Health & Safety, Privacy Act, Fair Trading, FMA. Flags issues before regulators or lawyers find them.
- 01 Reviews documents and recordings against your obligations
- 02 Risk scoring with explanations a manager can act on
- 03 Auto-redacts personal info in records you share externally
- 04 Audit-ready logs for WorkSafe, FMA, or Privacy Commissioner
Built on: Claude Vercel Postgres AWS S3
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 compliance monitoring 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 auto repair shops 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 compliance monitoring 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 pattern across most auto repair shops we work with.
- Mechanics quote from underneath a car and answer the phone from underneath a car, and one of those always loses.
- Booking, quoting, and parts follow-up are the admin layer that decides how many cars a workshop can turn over in a week.
How we build AI compliance monitoring for auto repair shops.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for an auto repair shop business, so value lands before the build is finished. AI compliance + audit.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing auto repair shops 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 auto repair shops
What changes for auto repair shops after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. Compliance review effort cut 70% with fewer escalations.
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 fast could we have AI compliance monitoring in production?
Eight to ten weeks for most auto repair shops. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for auto repair shops 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.
What's the realistic outcome for auto repair shops?
Compliance review effort cut 70% with fewer escalations. We don't promise tenfold lifts because we don't see them outside of marketing decks.
What if our auto repair shop doesn't have any data ready?
Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI compliance monitoring specifically, we typically run that work on Claude, Vercel, Postgres, AWS S3 and assume messy starting conditions from day one.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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.