FOR HOTELS
Train your hotel into AI.
The warmth of your property answers at 2am, in the room rates you actually sell, with the local picks your manager swears by. A specialized AI trained on your rooms, your house rules, and your voice — answering on every channel the guest already uses.
What it knows.
- – your rooms — class, bed configuration, view, square footage, accessibility, the rate you can actually quote tonight
- – your amenities — pool hours, gym access code, breakfast cutoff, parking validation, pet policy
- – your house rules — check-in window, quiet hours, the lost-key procedure, the right way to handle a late arrival
- – your local recommendations in your voice — the coffee place the manager actually likes, not a generic Google list
- – your booking and cancellation policy — direct, OTA, refundable vs. prepaid, group blocks
- – your loyalty program and house-account terms, if you run them
Where it shows up.
- – front-desk SMS, overnight, for the guest who locked themselves out of room 412
- – website chat for the late-night booking question, with the rate you can actually book
- – after-hours phone, with a calm voice that knows the property
- – group-booking inquiry intake — wedding blocks, corporate retreats, the questions you keep answering by hand
- – internal staff lookup — "what time does the gym open?" pinged from a housekeeping radio
- – pre-arrival confirmations and post-stay follow-ups drafted in your voice
A REAL 2AM
What a trained hotel AI actually says.
A guest is texting from the parking lot. Front desk is on a break in the kitchen. The AI handles identity, dispatches the re-key, logs the request.
2:14am Sat · Guest
2:14am · Trained AI
2:15am · Guest
2:15am · Trained AI
2:16am · Guest
Dialogue is illustrative. Identity verification, the re-key dispatch, and the request log are wired to your PMS once trained.
Before and after.
Before Gpodz
- – the overnight clerk handles re-keys, voicemail, and the chat widget alone; one of the three slips
- – after-hours booking questions wait until 7am — the guest already booked the OTA listing
- – "local recommendations" on the booking page is a generic Google paragraph
- – group-booking inquiries pile up; the sales manager is back Monday
After Gpodz
- – SMS, chat, voice, and group intake all answered in your voice, around the clock
- – booking questions answered with the direct rate, before the guest pivots to the OTA
- – local picks are the picks your manager actually makes — the coffee place that is open at 6am, not at 8
- – group inquiries logged and qualified by Monday morning, ready for the sales call
EARLY OUTCOMES
What we expect to measure.
Real numbers, once design-partner runs land. Placeholders below are explicit; we publish measured values, not projections.
- – direct-booking lift vs. OTA share: TODO % — measured against the same property's prior 30-day baseline
- – overnight front-desk hours recovered: TODO hours/week — replacing the chat + SMS + voicemail rota
- – group-booking lead response time: TODO (target: same-day) — Sprint 005+ design-partner data
- – post-stay-survey sentiment on after-hours service: TODO — paired pre/post baselines per property
Numbers will be replaced with measured values from design-partner runs once agreements sign and the training jobs complete.
A trained AI that knows your property beats a generic chatbot every time.
A generic AI does not know your room classes, your gym code, or the alley you tell late arrivals to park in. It writes a generic local guide that sounds like every other hotel within five miles. A trained AI quotes the rate you can actually book, names the room your guest is in, mentions the coffee place your manager actually likes, and switches to Spanish or Portuguese the moment the thread does. The hospitality warmth is yours — because the trained intelligence learned it from your voice, not a default one. It runs on shared infrastructure for a small fraction of frontier rates at SMB volumes.
Trust, quietly.
Three guarantees underneath every reply. The mechanics live on the trust page.
- – Eval-gated replies. If the AI is unsure about a refund, a comp, or a house-rule edge case, it routes to your front-desk lead instead of inventing.
- – Verifiable billing. Every charge is Ed25519-signed and verifiable offline. Designed to start at Ready.
- – Your data stays yours. Guest names, room logs, and your house playbook never train Gpodz platform models, never get pooled across tenants, never get sold downstream.
Same shape, next door.
Hospitality, in-the-room service, recurring relationships — the pattern repeats in the businesses next to yours.
- – Restaurants — reservation SMS, allergens, missed-call rescue in your house tone.
- – Medical spas — booking SMS, intake screening, contraindication checks in the front-desk voice.
- – Realtors — lead-follow-up SMS, listing drafts that know the neighborhood.
Train the AI that knows your hotel.
Start with one property. Ship it across every channel. Iterate from real guest conversations.