Most roofing 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 agents: not a tech showcase, but a careful look at the one or two workflows where a roofing company is paying for the same problem to be solved twice.
For roofing companies who want results in weeks, not a year-long transformation programme.
Our goal is to give roofing companies a three-day weekend, so people can spend more time with their families and the people they love :)
What AI agents actually does
Autonomous AI agents that don't just answer - they get things done. They check inventory, draft proposals, file paperwork, and chase quotes while your team focuses on the human work.
- 01 Goal-driven agents that complete multi-step tasks
- 02 Connect to your tools - Xero, HubSpot, Gmail, Slack, your CRM
- 03 Human-in-the-loop checkpoints for anything risky
- 04 Full audit log of every action the agent takes
Built on: Claude Agent SDK OpenAI Agents LangGraph n8n MCP
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 agents 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 roofing 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 agents 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 roofing companies we work with.
- Roofers quote off photos, chase weather windows, and juggle insurance jobs that all move at different speeds.
- Fast, accurate quoting from a photo is the single biggest lever for a roofing business's close rate.
How we build AI agents for roofing companies.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a roofing company business, so value lands before the build is finished. AI agents that do work.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing roofing 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 roofing companies
What changes for roofing companies 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. Replaces 15+ hours of weekly back-office work per agent deployed.
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 agents in production?
Eight to ten weeks for most roofing 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 roofing 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.
Can you walk us through a comparable build?
Yes - on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Replaces 15+ hours of weekly back-office work per agent deployed.
What if our roofing 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 agents specifically, we typically run that work on Claude Agent SDK, OpenAI Agents, LangGraph, n8n, MCP and assume messy starting conditions from day one.
One short call.
Tell us what you're trying to fix. We'll come back inside a working day.
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.