Case study

Customer Service & Job Scheduling AI

A multi-agent cleaning operations assistant that captures WhatsApp enquiries, checks customer records and job schedules, drafts replies, and prepares daily driver timetable support.

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Business problem

Customer enquiries need quick schedule checks, customer lookup, and clear reply drafting.
Cleaning teams must coordinate 11 cleaner calendars, travel buffers, and service-area rules.
WhatsApp messages can be missed during busy periods or after hours.

What the AI does

WhatsApp intake: captures booking, reschedule, and follow-up messages.
Jobber lookup: matches phone numbers to customer details, addresses, and context.
Scheduling support: checks cleaner availability, buffers, pairing rules, and serviced areas.
Human-approved replies: drafts friendly responses for the owner to review before sending.
Daily planning: supports driver timetable PDF generation for assignments and times.

Workflow

WhatsApp enquiry to schedule-ready reply

Tools

WhatsApp, Discord, Jobber, timetable PDFs

Value

Faster replies, fewer missed messages, cleaner daily operations

Example workflows

Customer message

WhatsApp captures a new booking, reschedule request, or late-night enquiry.

AI checks context

Customer records, address, service area, cleaner availability, buffers, and pairing rules are reviewed.

Team review

A ready-to-send reply and schedule summary are routed to the owner or operations team.

Schedule-ready output

The team confirms the booking, offers alternatives, or adds the enquiry to the morning inbox.

Next integration opportunities

Outbound WhatsApp replies after approval.
Jobber write access for booking confirmation.
Payment checks, accounting invoices, recurring visit management, and performance reports.