RevPAR is managed in weekly meetings, not real-time
Your competitors' systems adjust rates every 15 minutes based on live demand, weather, local diary, and comp set moves. You're leaving yield on the table every day.
+18%
RevPAR uplift in 6 months (Vantage Hotels)
−41%
Reception call volume after AI concierge
4.6★
Avg review score post-deployment (from 4.1)
[ Intro ]
The hotel that knows what a guest wants before they ask is the hotel they return to.
Hospitality has always been a data-rich industry. The problem hasn’t been a lack of data — it’s been the inability to act on it in real time, at the guest level, with the team you actually have.
A dynamic rate engine monitors your comp set, demand calendar, and booking pace — adjusting rates in real time, not in weekly revenue meetings. An AI concierge handles pre-stay questions via WhatsApp before reception arrives. Review intelligence categorises every incoming review and drafts an on-brand response in under 30 seconds.
The result: better yield, less administrative load, and guests who feel heard and served before they’ve even arrived.
[ The problem ]
What's quietly compressing hotel margins in 2026.
OTA commission continues to erode direct booking margin. Staffing costs are higher than ever. Guests’ expectations are rising faster than most independent and boutique operators can keep pace with.
The hotels winning aren’t competing on room count or location alone. They’re competing on intelligence — how fast they respond, how accurately they price, how personally they communicate.
Your team answers the same pre-stay questions on repeat
"Is parking free?" "What time is check-in?" Hours per shift on questions that don't need a human answer.
Review management is reactive and inconsistent
Most hotels respond to less than 40% of their reviews. The unanswered ones shape the next guest's booking decision.
Upsell opportunities go unrecognised
Most hotels send the same upsell email to every arrival. Personalised upsell is where significant ancillary revenue hides.
OTA dependency is growing, not shrinking
Direct booking rates are flat. Marketing budget consumed by OTA commissions rather than building your own guest acquisition channel.
[ AI Plays ]
Four AI plays that compound hotel performance.
Each system targets a specific revenue or experience lever. Most clients deploy two in the first engagement and add the others within six months.
Dynamic Rate Engine
A custom rate intelligence model that monitors your comp set, demand calendar, local event diary, booking pace, and weather signals — adjusting recommended rates in real time. Your Revenue Manager reviews and approves.
AI Concierge Agent
Pre-stay, in-stay, and post-stay guest communications via WhatsApp, SMS, or email — handled by an AI agent trained on your hotel's services, policies, and brand tone. Escalates complex needs with full context.
Review Intelligence & Auto-Response
Every review across every platform automatically categorised by sentiment, topic, and urgency. Positive reviews get an on-brand response within minutes. Negative reviews escalated with a draft response.
Personalised Upsell Agent
Triggered by stay context — first stay, anniversary, business trip, family booking — the upsell agent sends personalised offers at the optimal pre-arrival window.
[ How it works ]
How a hospitality AI engagement works.
Discovery & PMS Audit (Week 1)
We map your PMS, channel manager, review aggregator, and guest communication tooling. We identify the highest-ROI first deployment.
Build & Integration (Weeks 2–5)
AI systems built and integrated with Mews, Opera, Protel, Apaleo, or Clock PMS. Brand training and tone calibration.
Live Deployment & Team Onboarding (Week 6)
Systems go live. Revenue and front-of-house teams trained on monitoring and overrides. Runbook handed over.
Quarterly Optimisation (Ongoing)
Rate engine retraining. Review categorisation refinement. Upsell offer A/B testing. Performance review with leadership.
We went from manually checking comp set rates twice a week to having a live feed that adjusts recommendations every few hours. The RevPAR improvement paid for the entire engagement in the first quarter.
London Property Group 3× Their Qualified Leads in 90 Days
↗ 3× qualified pipeline in 90 days
Vantage Hotels Lifts RevPAR 18% With AI Rate Engine
↗ RevPAR +18% in 6 months
Northgate Capital Builds Connected RevOps in 90 Days
↗ Net revenue retention +12%
Houseguest Cuts Itinerary Quote Time by 55% With AI Builder
↗ Time-to-quote down 55%
Lumen Retail Ships 4,200 Product Pages in 6 Weeks
↗ 4,200 pages in 6 weeks
E-commerce Fashion Brand Scales to £2M Revenue With AI-Powered Retention
↗ £2M ARR within 2 quarters
[ FAQ ]
Common questions.
What PMS systems do you integrate with?
We've integrated with Mews, Opera, Protel, Apaleo, and Clock PMS, plus several custom systems. Most modern PMS platforms have an API — if yours does, we can connect to it.
Does the AI concierge replace our front desk team?
No. It handles the repetitive pre-arrival queries that don't need a human — freeing your front desk team for the moments that actually define the guest experience.
We're a small independent hotel — is AI cost-effective?
For hotels above 20 rooms, the rate engine and review intelligence typically deliver positive ROI within the first quarter. Our AI Launchpad is sized for independent operators.
How do you handle GDPR with guest data?
All data handling is covered by our DPA, aligned with UK GDPR. Guest data is never used for AI training.
Can the rate engine work alongside our revenue manager?
That's the intended model. The engine surfaces recommendations — your Revenue Manager approves, overrides, or adjusts. It augments judgement, doesn't replace it.
Your comp set is adjusting rates while you're reading this.
A 30-minute call is all it takes to identify your biggest revenue leak and give you a clear first step. No deck. No sales pressure.