Every building company business we've worked with has a different definition of "broken". AI recruiting only earns its keep when it solves the specific definition you'd give it on a bad day - which is why our first call is mostly listening.
Building companies-grade AI recruiting, shipped by people who've done it before.
Our goal is to give building companies a three-day weekend, so people can spend more time with their families and the people they love :)
What AI recruiting actually does
Job ads written for SEEK, Trade Me, and LinkedIn. CVs screened against role criteria with reasoning. Phone screens done by voice AI - so shortlists land on your desk ready to interview.
- 01 Drafts compliant NZ job ads with realistic salary bands
- 02 Screens CVs and ranks by fit with written rationale
- 03 Voice AI runs first-round phone screens 24/7
- 04 Bias checks built in - flagged in the audit log
Built on: Claude Vapi Workable SEEK API 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 recruiting 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 building companies 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 recruiting 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 |
Where building companies actually lose hours and dollars.
- Builders run multiple sites at once, and the paperwork behind each one grows faster than anyone has time to manage.
- Variations, supplier orders, and client updates are the admin layer that determines whether a build stays on schedule.
How we build AI recruiting for building companies.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a building company business, so value lands before the build is finished. AI candidate screening.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing building companies 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 building companies
Time-to-shortlist drops from 3 weeks to 4 days. For building companies, 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.
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 building companies 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 recruiting?
Plenty. Time-to-shortlist drops from 3 weeks to 4 days. 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 recruiting on?
For AI recruiting we usually reach for Claude, Vapi, Workable, SEEK API, Vercel. We're tool-agnostic at heart - we pick what your building company team can actually run after we hand the build over, not what looks good on a vendor sticker.
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.