Built around your PMS, not instead of itNothing auto-publishes to guests without rules you setAllergen data handled as verified fact, never inferredFixed monthly fee, cancel after 90 days

AI systems for hotels and hospitality groups

Enquiries arrive through the booking engine, the OTA extranets, a general inbox, Instagram, WhatsApp and the phone. Nobody owns all six, so the duty manager triages between check-ins and the wedding enquiry that came in on Sunday is still unopened on Tuesday. That's the problem worth solving.

01The problem

Tuesday morning in a hospitality business

Fourteen unanswered OTA messages, three of them asking whether you have a cot. A wedding enquiry from Sunday nobody has opened. Twenty-two reviews awaiting a reply. A supplier has changed the mayonnaise and nobody has updated the allergen sheet.

01

The enquiry inbox that never closes

Six channels, no single owner, and a response time that's measured in hours when guests expect minutes. Most of the questions are the same twenty questions, and the answers already exist in your PMS.

02

Group and event enquiries going cold

A wedding, an away-day or a private dining request arrives as free text: rough dates, rough numbers, a budget hint. Converting it means checking availability across rooms and function space and building a proposal. So it waits until someone has a clear hour — and by then the enquiry has gone somewhere that replied in ten minutes.

The single most expensive delay in the sector
03

Reviews answered in batches at 11pm

Google, TripAdvisor, the OTAs, OpenTable. Responding properly is a management task with no time allocated to it, so it happens late, generically, or not at all — and it's visible to every future guest.

04

Menu changes that ripple everywhere

One substitution and the allergen matrix, the labels, the website, the OTA descriptions and the staff brief all need updating. Miss one and it's a criminal offence, not a service failure.

02What we'd build

What we'd build for a hotel or group

One job at a time, built around the systems you already run, with your rules on what it may and may not say to a guest.

Build 01

Unified enquiry triage

Reads every inbound channel, classifies each message, extracts dates and party size into structured fields, and drafts a reply in your voice. Routine questions get answered in the same minute; anything sensitive routes to a person with a brief already prepared.

Typical setup 2–3 weeks.
Build 02

Group and event qualification

Turns a free-text enquiry into a structured brief — date, headcount, space, catering requirement, budget signal — checks the diary and produces a first-pass proposal your events coordinator edits rather than writes.

Where the revenue is.
Build 03

Review response drafting

Drafts platform-appropriate responses in your tone, and flags anything mentioning illness, injury, discrimination, allergens or theft for mandatory human handling. Nothing publishes automatically unless you decide it should.

Build 04

Allergen and menu propagation

When a dish or supplier changes, re-derives the allergen matrix from your verified ingredient data, produces the label text and issues the staff brief — with a named human sign-off recorded before anything goes live.

Sign-off is mandatory, by design.
Build 05

Rate and parity monitoring

A daily sweep of your OTA listings and comp set, flagging parity breaches, failed channel-manager pushes and competitor rate moves as a morning digest rather than another dashboard nobody opens.

Build 06

Pre-arrival and post-stay sequencing

Personalised messages that also collect dietary requirements, arrival times and upsell interest — and write them straight back into the PMS instead of into somebody's inbox.

03Governance

The rules that shape a hospitality build

Hospitality's regulatory exposure is concentrated in a few places, and one of them is genuinely life-critical. That dictates where automation stops.

Full governance, data residency and EU AI Act position →

04Hard limits

What we won't automate in hospitality

Hospitality is a people business and some conversations must stay human. These are the ones we'd refuse to hand over.

✕ 01

Giving a guest a final allergen answer

A model inferring “probably no nuts” from a menu description is a route to somebody being seriously harmed. AI maintains and surfaces the verified matrix. A trained human confirms it to the guest. We will not build it the other way round.

✕ 02

Auto-publishing responses to serious complaints

Anything mentioning illness, injury, safeguarding, discrimination or an allergic reaction is legal exposure, not reputation management. It goes to a person, always.

✕ 03

Refusal of service and age verification

Licensing obligations sit with named individuals for good reason. A system has no business making a judgement about whether someone has had enough or looks under 25.

✕ 04

Resolving a complaint escalation

Refunds, comps and upgrades are goodwill decisions made by a manager. A guest who's already been let down and is then handled by a bot has been let down twice.

05Questions

Common questions.

Is it safe to use AI for allergen information in a restaurant?

+

Not for the final answer to a guest — and any supplier who tells you otherwise is one you should walk away from. What AI can safely do is maintain the allergen matrix: when a dish or a supplier changes, it re-derives the affected entries from verified ingredient data, drafts the updated labelling, and issues the staff brief with a named person signing it off. The information a guest is given still comes from a trained human working off verified data. The automation removes the administrative gap where mistakes actually happen.

Can AI answer hotel guest enquiries?

+

Yes, for the large majority that are routine and factual — availability, parking, check-in times, cots, dog policy, directions. A well-built system reads the enquiry across whichever channel it arrived on, pulls the real answer from your PMS, and replies in your voice within the minute. The design work is in the exceptions: complaints, accessibility requests, group enquiries and anything medical route to a person with the context already assembled.

How does it connect to our PMS and channel manager?

+

Through the interfaces they already expose. Most property management systems and channel managers offer an API or a scheduled data exchange, and we build against that rather than asking you to change systems. Your team carries on working in the PMS they know; the AI reads from it and writes back to it.

Does this replace our reception or reservations team?

+

No, and we'd be sceptical of anyone promising it does. What it removes is the repetitive share of the inbox — the same twenty questions, answered a hundred times a week — so your team is dealing with guests rather than typing. In practice the visible change is response time on enquiries that used to sit for a day, and group enquiries getting a proposal the same afternoon.

How do multi-property groups roll this out?

+

One property first, then the rest. We build and prove the workflow at a single site — usually the one with the worst enquiry backlog — then extend it, with property-level differences in tone, policy and rate rules configured rather than rebuilt. That avoids the common failure of nine properties running nine slightly different systems nobody fully understands.

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Start here

Start with the inbox.

It's usually the fastest thing to prove and the easiest to measure. Tell us how many channels your enquiries arrive on and we'll tell you what's realistic.