Skip to content

AI for Travel & Hospitality

Guest requests, answered. Not lost to the quiet hours.

We engineer AI for hotels and hospitality groups: multilingual concierge that answers guests the moment they ask, dynamic pricing that reads live demand, upsell and cross-sell timed to the stay, and review and guest-messaging that reads like the brand.

Discuss your direct-booking and guest-experience workflowSee how the system works

The operational reality

A stay crosses booking, PMS, pricing, payments, messaging, housekeeping, and reviews.

Every seam is a chance for the guest to feel it. Every seam is a chance to lose them.

The best review is the one you never had to ask for.

Felt by directors of revenue, heads of guest experience, heads of front office, GMs of boutique and independent hotels, and the heads of direct distribution who absorb what weak response time and off-market pricing leave behind.

  1. 01

    Inquiry and booking

    A guest searches, lands on an OTA listing or the direct site, asks a question in chat or email, and either books directly, books on an OTA, or leaves.

    Friction · Inquiries arrive outside front-desk hours; a slow reply becomes an OTA booking at a higher commission.

  2. 02

    Pricing and distribution

    Rates, availability, and restrictions are published to the direct site, the OTAs, and the channel manager. Pricing adjusts to demand, events, and competitors.

    Friction · Rate changes land late on OTAs; the hotel undersells on peak nights and overprices on soft ones.

  3. 03

    Pre-arrival and arrival

    The guest receives pre-arrival messages, selects preferences and upsells, and arrives to a front desk that already knows them.

    Friction · Preferences, dietary needs, and loyalty tier live in different systems; the front desk rebuilds context on arrival.

  4. 04

    In-stay service and messaging

    The guest sends requests through SMS, WhatsApp, email, or the in-room app. Housekeeping, F&B, and the duty manager coordinate the response.

    Friction · Requests queue behind a shift change; a simple answer waits an hour and shows up in a review.

  5. 05

    Checkout, review, and follow-up

    Checkout is handled, the folio is sent, review platforms are monitored, and loyalty, repeat-stay, and referral offers go out.

    Friction · Reviews are responded to days late and in templates; the loyalty prompt lands when the stay has already faded.

Swipe the workflow

Where the work breaks

The friction is in the places nobody budgets for.

  • 01

    Inquiries at 2 am and on bank holidays go to a slow reply or an auto-responder.

    How we fix it · A system we build catches this before it costs you.

    Impact · The guest books on an OTA at a higher commission, or books with a competitor. The hotel pays for the inquiry twice.

  • 02

    Rate changes land on OTAs minutes or hours after they land on the direct site.

    How we fix it · A system we build catches this before it costs you.

    Impact · The hotel undersells on peak nights and leaves the direct channel at an avoidable disadvantage.

  • 03

    Guest preferences, loyalty tier, and prior-stay notes live in different systems.

    How we fix it · A system we build catches this before it costs you.

    Impact · The front desk cannot personalise the arrival; the guest feels anonymous on a stay the brand charges a premium for.

  • 04

    In-stay requests queue behind shift changes and housekeeping handoffs.

    How we fix it · A system we build catches this before it costs you.

    Impact · A simple request waits an hour, lands in a review, and drags the review score for a quarter.

  • 05

    Reviews are responded to days late with a template.

    How we fix it · A system we build catches this before it costs you.

    Impact · A thoughtful response window is missed; prospective guests reading the thread see a brand that does not pay attention.

What we would build

Systems, not features. Each with its own job.

  • 01

    Multilingual guest concierge across every channel

    Inquiries arrive in SMS, WhatsApp, email, and chat at every hour, in languages the on-shift team may not speak.

    Who benefits · Front-office teams, reservations, guest experience, and the duty manager outside business hours.

    Inputs
    The hotel policy library, room and rate pages, F&B hours, local area guidance, loyalty program rules, and the guest PMS record where consented.
    What the system does
    A retrieval assistant grounded in the hotel own content answers the common inquiries in the guest preferred language, drafts a response for the rest, and warm-routes anything sensitive, overbooked, or complaint-shaped to a named human.
    Output
    Grounded answers in-channel with the next action (book, upsell, confirm), or a warm handoff with a prepared summary when a person is the right responder.
    Benefit
    Response times fall from hours to minutes across time zones. Inquiries convert to direct bookings before they become OTA bookings.
    Human stays here
    Rate overrides, comps, upgrades, and complaint responses stay with a named human. The assistant discloses that it is an assistant.
  • 02

    Direct-booking recovery and OTA shift

    The OTA takes the booking and the commission because the direct site cannot answer the question that was blocking the decision.

    Who benefits · Directors of revenue, heads of direct distribution, and the digital team that owns the direct funnel.

    Inputs
    Live rate and inventory, the direct booking engine, the comparison against the OTA listing, and the specific inquiry the guest is making.
    What the system does
    The assistant answers the comparison question honestly, surfaces a direct-only benefit when it exists, and completes the booking on the direct site through the existing booking engine. Attribution is logged against the inquiry.
    Output
    Direct bookings captured in-channel at a lower effective cost, with the inquiry and the conversion attributed.
    Benefit
    Direct-channel share rises on exactly the inquiries that would have gone to an OTA. ADR holds; cost-per-booking falls.
    Human stays here
    Rate parity rules are respected. The assistant will not quote a rate the revenue team has not approved.
  • 03

    Dynamic pricing with reasons the revenue team can read

    Rates are set with a mix of spreadsheets, a legacy RMS, and gut feel. A soft night is priced like a peak one and a peak night is priced like a soft one.

    Who benefits · Directors of revenue, GMs, and the e-commerce lead who owns direct conversion at a given rate.

    Inputs
    Historical pickup, pace, booking window, segment mix, event calendars, competitor rates where legally available, and the hotel own revenue rules.
    What the system does
    A pricing layer proposes rate moves with the signals and reasoning behind each move, writes to the channel manager on approval, and tracks the outcome against the forecast.
    Output
    Rate recommendations with reasons, auto-published on approval, and a daily reconciliation of what moved and why.
    Benefit
    ADR and RevPAR respond to demand instead of to habit. The revenue team spends time on strategy instead of on manual rate loading.
    Human stays here
    The revenue team retains approval on moves above a configured delta. Rate parity, segment contracts, and promotional floors are hard constraints the system will not break.
  • 04

    Pre-arrival, upsell, and in-stay personalisation

    Upsell is a form at check-in or an email no one reads. Dietary needs and preferences are not visible until the server asks at breakfast.

    Who benefits · Heads of guest experience, F&B leads, front office, and the loyalty team.

    Inputs
    The reservation, loyalty tier, prior-stay notes, consented preferences, room allocation, and the live upsell inventory.
    What the system does
    The system drafts pre-arrival messages in the brand voice, offers upsells the guest is likely to accept, propagates dietary needs and preferences to F&B and housekeeping, and keeps the front desk brief one screen long.
    Output
    A pre-arrival sequence timed to the guest, a one-screen arrival brief for the front desk, and dietary and preference flags visible where they are needed.
    Benefit
    Upsell take rate rises on offers the guest actually wants. The arrival feels personal on a stay the brand charges a premium for.
    Human stays here
    Loyalty-tier benefits and comps stay with a named human. Dietary and medical sensitivities are surfaced, never inferred.
  • 05

    Review response and sentiment ops

    Reviews are responded to days late with a template. Review sentiment trends are visible only in retrospect and far too late to act on.

    Who benefits · GMs, heads of guest experience, and marketing.

    Inputs
    Review platforms (Google, TripAdvisor, Booking.com, Expedia), the hotel own response guidelines, prior reservation context where available, and the brand voice guidelines.
    What the system does
    The system drafts a tailored response in the brand voice for every review, clusters sentiment by theme and department, and surfaces operational issues before they show up in the score.
    Output
    Drafted review responses for a named human to approve, and a weekly operational briefing on what the reviews are actually saying.
    Benefit
    Response time to reviews falls. Operational issues are caught in the review stream before they drag the score.
    Human stays here
    Every public response is approved by a named human. The system refuses to draft a defensive or dismissive reply.

Show the system

What it could look like in your hands.

A design concept, not a shipped product. Interfaces like this get drawn out before any code lands, so the system reads back the way the people using it work.

front-desk / today

Booking queue

  • PK

    Deluxe king, 3 nights

    14:00 · Direct

    confirmed

    USD 1,290

  • SW

    Family suite, inquiry

    14:12 · OTA

    pending

    USD 2,040

  • MA

    Superior double, 2 nights

    15:00 · Phone

    confirmed

    USD 620

  • JL

    Executive suite, 4 nights

    15:30 · Direct

    confirmed

    USD 2,680

  • RB

    Deluxe king, late check-in

    15:45 · OTA

    waitlist

    USD 430

  • DN

    Standard queen, 1 night

    16:30 · Walk-in

    pending

    USD 210

JL

Executive suite, 4 nights

Loyalty Gold, 4 prior stays

Check-in 15:30, check-out Sunday, suite 812

Itinerary

  1. 15:30Welcome, suite walk-through, welcome amenity
  2. 19:00Dinner reservation at the hotel restaurant
  3. Day 2, 09:00Spa appointment, booked at pre-arrival
  4. Day 4, 11:00Late checkout approved per Loyalty Gold

Personalisation signals

Preferred floor
High floor, away from elevator
Last stay
Same suite, 11 months ago
Pillow preference
Firm, two per side
Local transport
Prefers airport transfer, prebooked

Dietary needs and loyalty on file

  • Shellfish allergy on file, flagged to F&B
  • Loyalty Gold: late checkout, lounge access, welcome amenity
  • Preferred language for messaging: English

Drafted upsell

Weekend spa package upsell at a Loyalty Gold rate

Reasoning · Guest booked the spa twice on prior stays. Package accepted on 5 of 7 similar Loyalty Gold profiles this quarter, and the suite rate leaves room for the offer.

Confidence72%
Synthetic data. This is a design concept of how a day of bookings and inquiries, a focused guest with their preferences, loyalty, and a drafted upsell, and an audited action pane could look at a hotel front desk.

End-to-end workflow

From the trigger to the outcome.

A representative path from an inquiry at 2 am to a repeat booking three months later. Automated stages run the moment the data lands; human stages are explicit, named, and never skipped.

  1. 01

    Inquiry arrives

    A guest message lands in SMS, WhatsApp, email, or the direct chat. Channel, language, and reservation context (where available) are attached.

    Automated
  2. 02

    Grounded answer

    The assistant answers the common inquiry in the guest preferred language with a source behind it, and surfaces a next step: book direct, confirm an upsell, or escalate.

    Automated
  3. 03

    Rate and inventory check

    Rate, availability, and parity rules are read from the booking engine before any price is quoted. The assistant will not quote outside approved rates.

    Integration
  4. 04

    Human escalation

    Rate overrides, comps, upgrades, complaints, and anything sensitive route to a named human with a prepared summary.

    Guardrail
  5. 05

    Direct booking

    If the guest books, the direct booking engine completes the transaction. Payment stays inside the existing PCI DSS boundary of the payment processor.

    Integration
  6. 06

    Pre-arrival sequence

    A pre-arrival sequence is drafted in the brand voice, offering upsells the guest is likely to accept and collecting preferences for the stay.

    Automated
  7. 07

    Arrival brief

    The front desk receives a one-screen brief: reservation, loyalty tier, preferences, dietary flags, and prior-stay notes.

    Automated
  8. 08

    In-stay messaging

    In-stay requests route through the duty manager and the right department. The assistant drafts, the duty manager approves and sends.

    Human in loop
  9. 09

    Review and follow-up

    A review response is drafted and approved by a named owner. A follow-up with a repeat-stay offer is timed to the guest.

    Human in loop

How exceptions are handled

  • If the assistant retrieval confidence is low, it returns 'not sure' and routes to the duty manager rather than guessing a policy.
  • If a guest flags a complaint, allergy, or safety concern, the assistant stops and escalates to a named human.
  • If the booking engine is unavailable, the assistant captures the intent and the stay dates, and reservations completes the booking manually.
  • If a rate change would breach parity or a segment contract, the system refuses the move and surfaces the conflict to the revenue team.
  • If a guest revokes consent, their messaging history and derived drafts are purged on the next job run.

How it is engineered

Built on your stack, not ours.

Design choices that make this run inside a real hotel operation, not a demo. We build to your PMS, your booking engine, your channel manager, and your payment processor, not to our stack.

01

PMS, booking engine, and channel manager

Direct integrations to the PMS and booking engine in use (Opera, Mews, Cloudbeds, Apaleo, SiteMinder, and others). Reads and writes go through the vendor interfaces; the channel manager stays the system of truth for distribution.

02

Payment and PCI DSS boundary

Card data stays inside the existing PCI DSS boundary of the payment processor. The assistant never sees a PAN; tokens or payment links are used where a transaction needs to happen in-channel.

03

Content and policy retrieval

The hotel policy library, room and rate pages, F&B hours, local area guidance, and loyalty rules are indexed into a per-tenant retrieval system. Every assistant answer carries a source.

04

Messaging and channel routing

Messages are sent through the channel the guest accepted (SMS, WhatsApp, email, in-app). Opt-outs propagate everywhere at once.

05

Pricing layer

A pricing service reads pickup, pace, booking window, segment mix, and event signals, and proposes rate moves with reasons. Writes to the channel manager require approval above a configured delta.

06

Observability and evaluation

Every assistant turn, drafted response, and rate move is logged with the model version and inputs. An evaluation harness watches for tone drift, answer accuracy, and rate recommendation accuracy against the realised pickup.

What the business will measure

Numbers the operator already watches.

We agree on metrics and baselines before building. These are the numbers a director of revenue, head of guest experience, or GM usually watches.

  • 01

    ADR and RevPAR

    Baseline today

    Current ADR and RevPAR by segment, channel, and day of week.

    How it moves

    Pricing responds to live demand with reasons the revenue team can read; direct-channel share rises on the inquiries that would have gone to an OTA.

  • 02

    Direct-channel share

    Baseline today

    Current share of bookings and revenue by channel, with the OTA commission cost per booking.

    How it moves

    The assistant answers the comparison question in the moment and completes the booking on the direct site through the existing engine.

  • 03

    Response time to inquiries

    Baseline today

    Current median and 90th percentile response time by channel and hour of day.

    How it moves

    A grounded assistant answers the common inquiries in minutes across time zones; escalations arrive with a prepared summary.

  • 04

    Upsell take rate

    Baseline today

    Current take rate on pre-arrival and in-stay upsells by segment and loyalty tier.

    How it moves

    Offers are timed to the guest and match the stay pattern; dietary and preference flags are respected so the offer fits.

  • 05

    Review sentiment and cancellation / no-show rate

    Baseline today

    Current review-platform average, sentiment by theme, and cancellation or no-show share by segment.

    How it moves

    Reviews are responded to in-window and in brand voice; operational issues are caught in the review stream before they drag the score.

Human in the loop

Oversight, safety, and the data boundary

Where the humans stay in control.

The system is designed around the compliance posture a hospitality operator already runs under. Nothing autonomous that should not be.

  • 01

    PCI DSS boundary

    Card data stays inside the existing PCI DSS boundary of the payment processor. The assistant never sees a PAN. Tokens or payment links are used where a transaction needs to happen in-channel.

  • 02

    GDPR and state privacy posture

    The system operates as a processor under contract. Consent for marketing, messaging, and profiling is captured and respected. Data subject access, correction, and deletion requests are supported. In the US we build against CCPA and the newer state analogues with the same mechanics.

  • 03

    Rate parity and segment contracts

    Rate parity rules, promotional floors, and segment contracts are hard constraints. The pricing layer refuses to publish a move that would breach them.

  • 04

    Human approval on money and comps

    Rate overrides, comps, upgrades, refunds, and complaint responses stay with a named human. The assistant drafts; a human approves.

  • 05

    Allergies, loyalty, and sensitivities

    Dietary and medical sensitivities on file are surfaced to F&B and housekeeping. Loyalty-tier benefits are honoured where they are earned, never inferred.

  • 06

    Brand voice guardrails

    Every assistant response and review draft runs inside the brand style and tone guidelines. The system refuses to draft a defensive or dismissive public reply.

Proof

Work we have shipped, and the shape of what we build.

Real engagements where we can speak to them, and representative use cases where we cannot.

  • Use case

    Turning search intent into direct bookings

    A proposed design, informed by a representative Stallwart engagement on search-driven acquisition: the inquiries that would have gone to an OTA are met with a direct-site experience that answers the comparison question honestly and completes the booking in-channel.

  • Use case

    Multilingual concierge across every channel

    A proposed design: an assistant grounded in the hotel content answers inquiries in the guest preferred language across SMS, WhatsApp, email, and chat, and warm-routes rate overrides, comps, and complaints to a named human.

  • Use case

    Review response and sentiment ops

    A proposed design: tailored draft responses in the brand voice for every review, with sentiment clustered by theme and department so operational issues are caught before they drag the score.

How the build runs

Scoped tightly, shipped in phases.

Fixed price per phase, approved before the phase starts. You own the content, the integrations, the pricing logic, and the deployment.

  1. 01

    Discovery

    Two to three weeks. We sit with revenue, front office, and guest experience, map the real workflow against the PMS and channel manager, and agree on the metrics and baselines the system will move.

  2. 02

    Prototype on real inquiries

    Six to eight weeks. One property, one segment, one proof of mechanism. The assistant runs on the hotel real content in shadow mode on live inquiries; the pricing layer proposes moves to the revenue team for approval.

  3. 03

    Production rollout

    Eight to twelve weeks per property. PMS and channel manager integration, payment boundary, messaging routing, review workflow, and the approval flow the revenue and guest-experience teams signed off on.

  4. 04

    Handover

    You receive the full source, the prompts, the retrieval index configuration, the integration code, the pricing rules, and the evaluation suite. A two-week walkthrough with your revenue, front office, and marketing teams closes the engagement.

  5. 05

    Optional ongoing support

    A fixed-term support agreement for content changes, vendor interface updates, and model drift. Never a retainer dependency.

Common questions

Answers before the first call.

01Which PMS and channel managers do you integrate with?
We build against the PMS, booking engine, and channel manager you already run: Opera, Mews, Cloudbeds, Apaleo, SiteMinder, and others. Reads and writes go through the vendor interfaces; the channel manager stays the system of truth for distribution.
02How is PCI DSS handled?
Card data stays inside the existing PCI DSS boundary of your payment processor. The assistant never sees a PAN. Where a transaction needs to happen in-channel we use tokens or hosted payment links, so the PCI scope is kept tight.
03Will the assistant quote rates and give refunds?
The assistant quotes rates only inside the parity and promotional rules the revenue team has approved, and will not override. Comps, refunds, upgrades, and rate overrides stay with a named human. The assistant drafts; a human approves.
04How does the dynamic pricing layer avoid breaking parity or contracts?
Rate parity rules, promotional floors, and segment contracts are hard constraints the pricing layer refuses to breach. Moves above a configured delta require revenue-team approval before they publish. Every move is logged with the signals and the reasoning behind it.
05What languages are supported, and how is tone handled?
The assistant answers in the guest preferred language where that language is enabled. Tone runs inside your brand style and voice guidelines, with evaluation on your actual content. If it does not read like you, we have not shipped yet.
See the other details on the FAQ page

Next step

A thirty-minute conversation. Bring one property and one moment that costs direct bookings or ADR today, and we will walk through what the first phase would look like, where the measurements come from, and what has to be true for your revenue and guest-experience teams to approve it.

Discuss your direct-booking and guest-experience workflow

Helpful to have on the call

Helpful to have on the call: the PMS and channel manager you run, one property with a response-time or direct-share pain point, and the person who owns the revenue or guest-experience metric you would like to move.

Explore

A different problem in every sector, one engineering standard underneath.

Featured · AI for healthcare

Healthcare

Why is your clinician still charting at midnight?

Your clinicians are charting until midnight and your front desk is drowning in prior auths. We build AI that writes clinical notes automatically, triages patients to the right care faster, and finds any record with a simple question, so your people spend their hours on patients instead of paperwork.

See AI for healthcare
stallwart / healthcare

Live run

Healthcare

Running
as of nowhealthy
See every industry we build for

An AI-First Engineering Company

Get a price in one call.

One 30-minute call. You leave with an architecture, a fixed price, and a start date. No charge, and no slide deck.

Booking now for December 2026

Book a callSee how it works