Public demos use sample data. Live bookings require business setup; missed-call texts require provider routing and explicit consent. Reminders, deposits, abandoned-booking recovery, and analytics are not available. Feature availability
Turn website visitors and missed calls into booked repair jobs.
RepairSlot gives repair and service businesses a customer-facing booking layer for configured service windows, service-choice intake, and website booking after activation. Missed-call texts require separate provider setup and caller consent.
A repair appointment is more than an empty calendar slot.
Before a time is shown, RepairSlot can collect the repair type, service address, duration and other details your team needs. That makes it a better fit for field repairs than a generic meeting scheduler.
- Repair-specific intake
- Service-area validation
- Technician and duration-aware windows
- Private confirmation/cancellation link; no reminders
- Existing website integration
Book a repair
One platform, repair-specific workflows.
Offer appointments the team can actually keep.
RepairSlot starts with the selected job, location, expected duration, and available capacity. That lets a business offer controlled service windows instead of exposing a generic calendar that ignores travel and job complexity.
- Different durations for diagnostics, maintenance, and repairs
- Service-area checks before availability appears
- Capacity based on technicians or other limited resources
- Buffers for travel, overruns, and emergency calls
Add customer scheduling without replacing dispatch or invoicing.
The booking layer can start with common services and available windows while the team keeps its current CRM, field-service, accounting, and dispatch tools. Hosted pages launch fastest; embeds and widgets keep booking visible on an existing website.
Compare scheduling software with field-service management, or review the technician availability workflow.
Check the numbers before opening more appointment windows.
Use the free calculators to estimate theoretical capacity, then reduce it using actual travel, callback, and overrun data.