Most building companies we talk to aren't short of dashboards or tools - they're short of an hour back in the week. That's the lens we put on AI HR assistant: not a tech showcase, but a careful look at the one or two workflows where a building company is paying for the same problem to be solved twice.
Building companies-grade AI HR assistant, 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 HR assistant actually does
An AI HR assistant trained on your policies, awards, and the Employment Relations Act. Answers staff questions, drafts contracts, screens applicants, and flags HR risk - without replacing your people lead.
- 01 Answers leave, pay, and policy questions 24/7
- 02 Drafts contracts, warnings, and PIPs from templates
- 03 Screens CVs against role criteria with reasoning
- 04 Flags ER risks before they become disputes
Built on: Claude Employment Hero API BambooHR 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 HR assistant 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 HR assistant 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 two or three things that decide whether this works for building companies.
- 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 HR assistant 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 HR and people ops.
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
If we build the right slice first, building companies feel the difference inside the first month. HR enquiries drop 65% in the first month - leaders get their week back.
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 HR assistant in production?
Eight to ten weeks for most building companies. 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 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 HR assistant?
Plenty. HR enquiries drop 65% in the first month - leaders get their week back. 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 if our building company 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 HR assistant specifically, we typically run that work on Claude, Employment Hero API, BambooHR, Vercel 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.