What the receptionist captures
- Scope
- Address or service area
- Photos or access notes when applicable
- Preferred quote window
Use case
Quote Request Intake
Quote requests arrive with missing details and create back-and-forth before anyone can respond.
Live call path
Quote Request Intake
Live intake
Incoming call
Scope, Address or service area, Photos or access notes when applicable captured before routing.
Outcome created
The call becomes a review-ready quote request with the details staff need first.
Context captured
Next step
- Create a quote request
- Route site-visit needs
- Attach caller context
Guardrails
What happens next
- Create a quote request
- Route site-visit needs
- Attach caller context
Guardrails
- No final quote on the call
- No timeline or availability guarantees beyond configured rules
Industry fit
Best-fit industries
Where this workflow usually fits.
Junk Removal
For hauling teams that need item lists, pickup windows, crew-capacity notes, and quote handoff.
Open industry pageCleaning and Pressure Washing
For cleaning, janitorial, and pressure-washing teams that need quote windows and qualified requests.
Open industry pageLandscaping and Lawn Care
For outdoor crews capturing seasonal requests, property context, quote windows, and site visits.
Open industry pageRoofing, Siding, and Exterior
For exterior teams handling storm calls, leak intake, inspection windows, and insurance-heavy review.
Open industry pageGeneral Contractors and Renovations
For contractors turning project calls into scoped notes, callbacks, and site-visit requests.
Open industry pagePut it on a real call path
See how it sounds in the demo.
The public demo is mock-only, but it shows how an AI receptionist captures context and creates a next step without touching real customer records.