Housekeeping & Maintenance Ops · Documentation

Business Problem & Solution

The problem Housekeeping & Maintenance Ops solves in the hospitality ecosystem and how this downscaled demo proves it.

Housekeeping & Maintenance Ops
incoming workthe systemtracked workdispatched (#07)scheduled tasksthe roster (#43)auto-assignskill · shift · loadSLA work ordersa best-match assigneea status boardwork routed, not piled up
Live diagram — a request confirmed in #07 becomes an auto-assigned work order here, idempotently, even when this tab is closed.

The problem — work arrives faster than it gets assigned

Housekeeping and maintenance work arrives two ways — dispatched from on-property service triage (app 07) and as scheduled tasks — and both pile up faster than a manager can route them by hand. The bottleneck is assignment: matching each job to someone with the right skill, who is actually on shift, and who is not already buried. App 14 owns that: it turns dispatched requests and scheduled tasks into SLA-stamped work orders and auto-assigns each to the best available person.

What this demo proves — and what it simplifies

It proves the live spine: a request confirmed in app 07 emits `service.requested`, and app 14 creates and auto-assigns a work order from it — idempotently, even when 14's tab is closed. The assignment itself is deterministic and $0 (AI-assist, not a metered model): it ranks staff by skill match, on-shift status (read from app 43's published roster), and current load. It simplifies the field: there are no real staff devices or notifications — assignment, status transitions and SLA tracking are real; the dispatch to a human is stood in for and labelled.

Business Problem & Solution · Housekeeping & Maintenance Ops · Abhishek Saxena