Industry · Hospitality

Faster guest service, with every billable change approved.

Agents read reservations, weigh seating options, and set up guest requests — routing every billable change through its own approval and audit.

How the governed layer helps

Control is the default here.

At the front desk, a request like “this guest wants a late checkout and a room-service order — set it up” becomes a plan card: a read-only reservation lookup, then a separate approval card for each billable change before anything is committed.

At the host stand, a reservation and waitlist assistant compares open slots, creates a booking as a low-risk create, and sends a guest notification through approval — so there’s no accidental spam.

General managers get property analytics — covers, average check, and revenue by daypart — from one plain-language question, scoped to their property and auditable.

Every action an agent takes here runs through the same gate: least-privilege permissions, policy and an audit trail, with the sensitive steps held for human approval. The controls behind it are set out on the security and data-handling page.

Example agents & workflows

What it looks like in practice.

Illustrative examples of what a host would configure — tool ids and risk levels are the host’s to define. The primitives underneath are built and tested.

Example

Front-desk guest request assistant

Two approval cards, one per billable change — late checkout and room service — before anything is committed to the reservation.

Example

Reservation & waitlist assistant

A slot-option comparison, then an approved guest text; the booking is a low-risk create, the notification is approval-gated.

Example

Covers & revenue report

Specialist agents return a daypart revenue table and a trend diagram from a single question — no BI seat.

See governed AI for Hospitality & food service.

Book a demo and we’ll tailor the walkthrough to your sector — the governance model, the two-seam integration, and an example close to your systems.