AI solutions for hospitality that work inside your PMS, POS and WhatsApp
We build AI solutions for hospitality groups: a hotel AI assistant that books a room, orders room service and handles checkout in English, Arabic or Tamil; a restaurant ordering assistant on web chat and WhatsApp; and occupancy and staffing forecasts your general manager can act on. Each connects to the property management, point-of-sale and booking systems you run today.
Hospitality demand swings, and the systems do not talk
A hotel sells the same room through its website, three travel agencies and a corporate contract, serves breakfast from a POS that has never heard of the PMS, and staffs the desk by last year's calendar. Guests expect an answer at 2 a.m. in their own language. AI in hotels pays off when it completes tasks across those systems, not when it adds a chat window.
Where we deliver: in UAE, for hotels under the Department of Culture and Tourism Abu Dhabi and Dubai tourism rules, handling guest data under UAE PDPL; in Saudi Arabia, for operators scaling with the Vision 2030 tourism targets under the SDAIA PDPL and NCA ECC-2:2024; in India, for hotel and restaurant groups handling guest records under the DPDP Act 2023 and GST e-invoicing; and in United States, for properties handling card data under PCI DSS and state privacy laws. Offices are on our locations page.
Six hospitality workflows we build, from guest message to staffing plan
Two are products you can see in a demo; the rest are engineered around your systems.
Hospitality-specific AI assistance
A24 Hospitality Intelligence is our multi-tenant hotel assistant: room booking, room service, food ordering, feedback and checkout intents, with Indian-language speech and an outbound voice agent for confirmations.
Guest inquiry and concierge workflows
Guest questions about late checkout, spa slots or airport transfers answered from approved content and completed in the PMS or task system, with a handoff to the duty manager carrying the full conversation.
Learn more →03Occupancy and demand insights
Occupancy, average rate and food-and-beverage demand forecast by property and day, with event calendars and booking pace as inputs and error reported in rooms.
Learn more →Restaurant queue and workload analytics
Order volume, kitchen throughput and table turn from POS data, with the AI Restaurant Ordering Assistant taking orders on web chat and WhatsApp so staff are not typing during the rush. Restaurant AI ordering with the kitchen in view.
Staffing and operational forecasting
Front desk, housekeeping and kitchen rosters shaped by forecast arrivals, departures and covers. The schedule is a proposal the department head edits, not an automatic change.
POS, PMS and booking integration
Integration services between property management, point-of-sale, booking engines and channel managers, so an assistant's booking appears in the PMS and a room-service order reaches the kitchen printer.
Learn more →Agentic AI and hospitality product engineering under one roof
Our hospitality work rests on a platform we built ourselves: LangGraph and LangChain agents with PostgreSQL checkpointing, Redis sessions, WebSocket and gRPC microservices, speech-to-text and text-to-speech for Indian languages, and an outbound voice agent over telephony. We benchmarked intent classification between LLM and retrieval approaches before choosing.
Around that platform sit the same analytics, integration and application teams who build our other industry work, so a guest experience AI project arrives with its forecasts, PMS connectors and monitoring already designed.
A worked example: from unanswered WhatsApp messages to a booked, served and checked-out guest
Suppose a multi-property group receives WhatsApp messages that go unanswered overnight. Here is how that becomes a multi-tenant assistant completing bookings and room-service orders in the PMS and POS.
- 01
Measure the response gap
Overnight response time, abandoned booking inquiries and room-service calls to a busy desk are counted for two properties, which become the pilot.
- 02
Map PMS, POS and channels
Property management, restaurant POS, booking engine and WhatsApp Business accounts are mapped for APIs and for which actions may be automated without staff approval.
- 03
Define intents and success measures
Booking, room service, food ordering, feedback and checkout intents are prioritized, with targets for response time, completion without handoff and guest rating.
- 04
Prototype on real conversations
Anonymized message history tests intent routing. Arabic, English and Tamil are checked with native speakers from your staff, and the human handoff is exercised deliberately.
- 05
Validate guest data handling
Consent capture, residency per market, retention and access to conversation logs are reviewed under UAE PDPL, the SDAIA PDPL and the DPDP Act 2023 with your legal team.
- 06
Integrate and go live on two properties
Bookings post to the PMS, orders reach the kitchen POS, feedback lands in your guest system, and the duty manager sees a live handoff queue.
- 07
Monitor and roll out
Completion rate, handoff reasons and guest ratings are reviewed weekly. Properties are added in groups once the first two hold through a peak season.
How value is measured in a hotel or restaurant
Success is counted in response time, tasks completed without a handoff, staff minutes returned to guests, forecast error in rooms or covers and the guest rating after an assistant conversation. The baseline comes from your message logs and PMS reports before go-live, and we test on a sold-out weekend, Ramadan dining hours or a wedding block arriving at once. If an intent cannot reach the agreed completion rate it stays with staff.
Governance for guest data, payments and voice
Guest conversations contain names, room numbers, dietary needs and sometimes card details, so we treat them as personal data from the first message. Consent is captured in the channel, logs are retained to an agreed schedule, card data never passes through the assistant, and every automated booking or order is logged with the system it changed.
By market: UAE PDPL and tourism authority requirements in UAE; the SDAIA PDPL and NCA ECC-2:2024 in Saudi Arabia; the DPDP Act 2023 and GST e-invoicing in India; and PCI DSS and state privacy laws in United States. Voice recordings follow the same rules, with notice at the start of a call.
Why hospitality groups work with Constient
Because we built the hospitality intelligence platform ourselves and we integrate it ourselves, so there is no gap between the product team and the people wiring your PMS. Multi-tenant design means a group onboards properties with configuration, not a new project each time. Completion rate, response time and ratings are measured on your properties rather than promised, and both assistants can be seen in our product demos before any commitment.
Frequently asked questions
How does a hospitality AI engagement with Constient start?
With a discovery call and a review of one or two properties: message volumes, PMS and POS versions, languages your guests use and which actions you are comfortable automating. We then scope a fixed-price pilot on those properties with a baseline from your own logs. A demo of both assistants is available before discovery.
Which PMS and POS systems can you integrate with?
Any system with a documented API or integration program, which covers the major cloud property management and point-of-sale platforms. Where an API is missing or licensed separately, we confirm cost and access in discovery and can fall back to email or file-based capture for the pilot. The booking must land in your PMS, not a separate inbox.
Which languages does the hotel AI assistant support?
English and Arabic for text and voice, plus Indian languages including Tamil and Hindi with speech recognition and synthesis built into our platform. Language quality is tested with native speakers from your staff during the pilot, and the assistant hands off to a person when confidence drops.
Where is guest conversation data stored?
In your region and tenant: in-country for UAE and Saudi properties, in India for Indian groups, and in your chosen US region for American properties. Conversation logs are retained to a schedule you set, card data never passes through the assistant, and access to logs is role-based and audited. Data flows are documented for your legal team.
How are the hospitality products priced?
A24 Hospitality Intelligence and the AI Restaurant Ordering Assistant are licensed per property or outlet on a subscription basis, with implementation and integration priced as a fixed-scope project once systems and property count are known. Custom forecasting work is a fixed-price pilot followed by a build or a dedicated team billed monthly.
Can the assistant take restaurant orders over WhatsApp during a rush?
Yes, that is what it is for. Guests order on web chat or WhatsApp, the assistant confirms items and modifiers against your menu, and the order reaches the kitchen through the POS. Staff see an exception queue for anything unusual. Throughput is measured during the pilot on your busiest service.
Build a hospitality technology roadmap starting with two properties
Bring the unanswered messages, the staffing problem or the restaurant rush. We will map your PMS and POS and propose a bounded pilot.