Guest requests that arrive with an owner and a clock.

• 01

  Structured request fulfilment

  Housekeeping, maintenance, amenities and F&B requests captured as typed work items with SLA clocks — not as chat messages someone has to re-read.

• 02

  Pre-arrival and in-stay questions

  Check-in times, parking, wifi and facilities answered from the property's own FAQ in the guest's language, at any hour.

• 03

  Escalation with context

  Anything outside the fixed menu becomes an owned item with the conversation attached, so the guest isn't asked to repeat themselves to a human.

• 01

  Grounded answers only

  The assistant answers from the property's own FAQ and nothing else. No general knowledge about what hotels usually do — that's precisely how a bot invents a spa you don't have.

• 02

  A fixed menu of actions

  Structured request types the system can actually fulfil, plus an explicit fallback so nothing stays unclassified. Open-ended action space is where guest-facing AI goes wrong.

• 03

  Every request gets a clock and an owner

  Response and resolution tracked as separate SLAs against a named staff member, so 'the bot handled it' is never the last thing anyone knows.

1. 1

   Use-case scoping

   Pick the workflow with the strongest ROI. Define success metrics, guardrails, and integration points.

2. 2

   Tools & memory

   Connect the agent to your real systems — CRM, helpdesk, data warehouse, internal APIs — with auth and audit trails.

3. 3

   Eval suite

   Build a versioned eval set from real conversations so we can prove the agent improves before each release.

4. 4

   Pilot with humans

   Shadow mode → suggested replies → autonomous on low-risk tasks. Humans stay in the loop where it matters.

5. 5

   Production scale

   Monitoring, fallbacks, cost guards, and observability. Weekly improvement cycles based on production data.

• Property management systems
• WhatsApp Business API
• QR-based guest web
• Native staff apps with push
• Booking engines & OTA feeds
• Twilio voice
• Revenue management tools

FAQ

AI guest messaging agents for hotels: your questions.

• What if the guest asks something the FAQ doesn't cover?

  It says so and creates a work item for staff. Refusing well is more valuable than answering confidently — a wrong answer about a dietary restriction or an accessibility feature is a real incident.

• How do staff actually receive these?

  On a native app with push, with the two SLA clocks visible. Requests routed into an email inbox go the same way verbal ones do — which is the problem this is meant to fix.

• How is this different from a chatbot?

  Chatbots reply. Agents act. Our agents call APIs, update records, send emails, schedule meetings — with audit logs and rollback. They take actions in your systems, not just respond in a chat window.

• Which LLMs do you use?

  We pick the right model for the task — Claude Sonnet/Opus for reasoning, GPT-4o for tool use, Llama / open-weights when data residency demands it. We're not locked into any vendor and we'll tell you what's cheapest at your volume.

• RAG for hotel and travel contentRetrieval scoped to your own FAQ, policy and destination content — multilingual, cited, and explicitly silent where the content doesn't exist.Read
• 30-day AI sprint for hospitalityScope it to a single property and the highest-volume request types. In 30 days you get working software running on real guests, with the numbers to decide about the rest of the estate.Read

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• AI agents for healthcare operationsAgents that handle scheduling, reminders, insurance verification and document chase across voice and messaging — escalating anything clinical to a person immediately.Read
• AI customer service agents for e-commerceSupport agents connected to orders, carriers and your returns rules — resolving tracking, exchanges and address changes end to end on Gorgias, Zendesk or Intercom.Read