Voice AI for Hospitality

A voice agent that answers every inbound call to the front desk phone number immediately, without hold music and without routing failures. The agent handles the calls that make up the bulk of inbound volume: check-in and check-out time questions, room type and rate confirmation for live reservations, local restaurant and attraction recommendations from a curated property knowledge base, parking and transport directions, hotel facility hours for pool, gym, spa, and restaurant, and escalation to a live front desk member when the request falls outside the agent's scope.

The agent connects to your property management system via REST API to look up reservation details in real time, a caller who gives their name or reservation number gets an immediate, accurate confirmation of their booking, not a generic holding message. Property knowledge base content is maintained in an admin interface so your team updates hours, promotions, and local recommendations without developer involvement. Call handling is available 24 hours a day, which means after-hours calls are handled rather than dropped to an answering machine. For multi-property groups, a single voice agent deployment provides consistent front desk support across all properties. Escalation handoff is handled cleanly, the agent tells the caller it is transferring them, summarises the interaction for the staff member receiving the call, and completes the transfer. Call logs with transcripts and resolution outcomes are stored and accessible from the management dashboard.

A voice bot that processes reservation modifications, cancellations, and confirmations without requiring a staff member to look up the booking, apply the change, and send a confirmation. The guest calls or is called by an outbound pre-arrival workflow, identifies themselves by name or reservation number, and the bot retrieves their booking from the PMS in real time. Date changes, room type changes, and cancellation requests are processed within the conversation, with cancellation policy rules applied automatically from the PMS so the guest is informed of any applicable charges before confirming.

Confirmation messages, SMS or email, are triggered immediately when the modification or cancellation is committed to the PMS, so the guest has a written record of what changed without having to wait for a staff member to manually send it. For simple requests like confirming arrival time, the bot reads the booking and confirms, closing the call in under 90 seconds. Outbound pre-arrival calls are triggered 24 hours before check-in from a configurable schedule: the bot calls the reservation's phone number, confirms arrival time and any special requests on the booking, and gives the guest the opportunity to modify or add requests before they arrive. This outbound flow reduces the check-in call volume that typically spikes on the morning of a busy arrival day.

An in-room voice assistant deployed on a dedicated device or accessible through the hotel app that handles service requests from within the room. The guest speaks the request, additional pillows, room service order, wake-up call for 7am, request for the bill, late checkout enquiry, and the assistant logs the request directly into your housekeeping management system or PMS via API. The guest receives a verbal confirmation with the expected fulfilment time based on current operational workload, and a member of staff receives the task on their housekeeping or service management app.

The assistant draws from a property knowledge base for queries that do not require a logged request: pool hours, gym location, restaurant reservation enquiries, local taxi booking instructions. Upsell prompts are built into the conversation design at natural points, when a guest asks about the restaurant, the assistant can mention that a dinner reservation is available tonight and offer to check availability. The conversation is designed to feel like talking to a member of staff, not navigating an IVR menu. Wake-up call scheduling, outbound calls, and DND status management are all handled in real time through the PMS API. All in-room interactions are logged and accessible in the management dashboard, giving the operations team visibility of request volumes, fulfilment times, and common guest queries.

A voice concierge that handles the local knowledge and experience booking requests that make up a large share of front desk and concierge desk call volume. The agent draws from a curated destination knowledge base for the property: restaurant recommendations with cuisine type, price range, and distance; activity and attraction information with booking links or phone numbers; transport options including taxi, rideshare, and public transport; and event and venue information for local calendar highlights.

For experience and activity bookings where a reservation is required, the agent can initiate a booking workflow, either by calling the venue on the guest's behalf using a call transfer, by sending the guest a booking link via SMS, or by triggering a concierge task in the hotel's task management system for a staff member to complete the booking. The knowledge base content is property-specific and maintained through an admin CMS, your concierge team adds and updates recommendations without developer involvement. Multi-language support covers the major language pairs in your guest mix, with language detection from the first phrase of the conversation. The concierge agent is available 24 hours, so late-evening dinner booking enquiries and early-morning transport requests are handled without requiring a staff member to be at the concierge desk.

Outbound and inbound voice flows that handle the administrative work of check-in and check-out without consuming front desk time. The pre-arrival outbound call, triggered 24 hours before check-in, confirms the guest's arrival time, reads out any special requests on the booking, reminds the guest of their room type and rate, and asks whether they would like to add any pre-arrival requests. The guest's responses update the PMS reservation record so the front desk sees the confirmed arrival time and any new requests without a manual note.

At check-out, an outbound call or inbound IVR flow handles the express check-out process for guests who do not need to query their bill: the agent confirms the total amount from the folio, asks the guest to confirm check-out, and commits the check-out to the PMS with a payment charge applied to the card on file. Guests who have a bill query are transferred to the front desk with a summary of the folio read out. The check-out flow reduces queue length at peak departure times and allows guests to check out from their room rather than waiting at the desk. Integration with digital key systems, SALTO, Dormakaba, Nuki, deactivates the room key at check-out confirmation so access control stays synchronised with the PMS without a manual desk process.

Voice agents that detect the caller's language from the first spoken phrase and continue the entire interaction in that language without requiring the guest to navigate a language menu. Language detection and switching is handled automatically using ElevenLabs' multilingual voice models and Deepgram's transcription models, which support major language pairs accurately in conversational hospitality dialogue. The same underlying agent logic and PMS integration operates across all supported languages, the guest experience is consistent whether the call comes in English, Spanish, French, German, Mandarin, or Japanese.

Multi-language support is particularly relevant for resort and city hotel properties with international guest mixes, where a guest's language preference is not predictable from the reservation channel. The agent is configured with the property's voice and tone standards in each language, not a direct translation of an English script but a conversation design appropriate to the hospitality register in each language. Voice selection per language uses ElevenLabs voices calibrated for warmth and clarity in hospitality contexts. The management dashboard shows call volume and resolution outcomes segmented by language, giving the operations team visibility of which language pairs are most active and whether specific language-pair interactions have higher escalation rates that might indicate a dialogue gap.