Most cleaning 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 receptionist: not a tech showcase, but a careful look at the one or two workflows where a cleaning company is paying for the same problem to be solved twice.
Cleaning companies · Applied AI
Built for the cleaning company who's already tried the off-the-shelf option and bounced off it.
What AI receptionist actually does
A 24/7 AI receptionist that answers calls and chats, books appointments, takes deposits, and routes urgent issues to a real human. Sounds Kiwi. Doesn't fumble names.
- 01 Voice + chat, both trained on your business
- 02 Knows your services, prices, and availability
- 03 Books direct into your calendar – no double-bookings
- 04 After-hours coverage with morning summary email
Built on: Vapi Twilio Claude Cal.com Stripe
Without Kiwi Dynamics
With Kiwi Dynamics
Sector context
Where cleaning companies actually lose hours and dollars.
- 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 receptionist 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. 24/7 AI front desk.
Talk to usThe outcome for cleaning companies
If we build the right slice first, cleaning companies feel the difference inside the first month. Captures the 30-40% of enquiries that used to go to voicemail.
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.
Questions
FAQ
How fast could we have AI receptionist in production?
Eight to ten weeks for most cleaning 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 cleaning 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.
Do you have proof this works for cleaning companies?
Direct case study: Captures the 30-40% of enquiries that used to go to voicemail. Happy to walk you through full numbers on a call.
What if our cleaning 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 receptionist specifically, we typically run that work on Vapi, Twilio, Claude, Cal.com, Stripe 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.
Get in touch
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.