There is a version of AI agents that cleaning companies buy off a shelf and quietly stop using inside a month. Then there's the version that's wired into your real workflow, owned by a person on your team, and still in use a year later. We only build the second one.
The version of AI agents that cleaning companies still use a year after launch.
Our goal is to give cleaning 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 cleaning 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 |
Where most cleaning companies engagements actually deliver value.
- Cleaning businesses run on recurring contracts and one-off quotes, both of which need fast, consistent follow-up to win.
- Quote turnaround and scheduling reliability are what most decide whether a cleaning company keeps a client past the first job.
How we build AI agents for cleaning companies.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a cleaning 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 cleaning 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 cleaning companies
We'd call the engagement a success when cleaning companies are using the system without thinking about us. 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 long does AI agents take to ship for cleaning companies?
We aim for a working pilot inside 4-6 weeks - narrow scope, real cleaning companies data, measurable outcome. From there it's another 6-8 weeks of hardening before you'd consider it production. Full rollouts (multiple sites, multiple teams) typically land in 3-4 months.
How do you price AI agents 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 cleaning companies are surprised how small the first cheque is.
Do you have proof this works for cleaning companies?
Direct case study: Replaces 15+ hours of weekly back-office work per agent deployed. Happy to walk you through full numbers on a call.
Who owns the code and the model setup?
You do, on delivery. We deploy AI agents into your own cloud account where possible, with the model setup, prompts, evals and integration code all checked into a repo you own. Claude Agent SDK sits in your account too - we don't operate it from ours.
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.