# Otel AI, full site content Last updated: 24 August 2026 Source: https://www.otelai.com Canonical origin: https://www.otelai.com (use www) Short version: https://www.otelai.com/llms.txt Otel AI is an AI layer for hotels. It connects the systems a hotel already runs on, reads them as one hotel rather than as separate tools, and hands the team decisions with the case already made. This file is a plain-text dump of the site's main pages, generated from the rendered pages themselves so it cannot drift from what visitors actually read. Blog posts are not reproduced here; they are listed at https://www.otelai.com/resources and every one is in the sitemap. Legal entity: TMBTP Limited, trading as Otel AI. 61 Thomas Street, Dublin 8, D08 W250, Ireland. Contact: hello@otelai.com --- ## Homepage URL: https://www.otelai.com/ The operating advantage for hotels. # The AI layer that gives your mornings back Otel reads every system your hotel runs on as one hotel, then hands your team each decision with the case already made. Book a demo → Chat ## Ask Otel anything What are the top most important insights you can give me about the business? Grendon Castle Opus 5 High How does pickup compare to last year? What needs my attention today? How are we pacing this month? What's net revenue after commission? Where are we behind budget? Results ## Measured in hotels running Otel. See more customer stories ↗ +8.6% RevPAR in three months 20+ Hours a week back from manual reporting 100+ Hotel systems connected, including legacy 10× Output on the same headcount The work ## Designed to take the work off your team. Supercharge your team. Gain real efficiencies. Get your mornings back. ### One operational layer. Otel connects the systems you already run and reads them as one hotel. Nothing migrates, nothing gets replaced, even the ones with no API. What needs my attention today? Running cross-department check Revenue .38s Comp set Marlin House dropped $30 Saturday. Created ops task: review rate signage. Group block Westmoor block still at 0%, 33 days out. Flagged to Roisin. Payroll .47s Labor Bar labor 5.2% over target, 3rd day. Routed to Conor for sign-off. Roster Three extra staff, no revenue lift. Looped in Catherine. Guest 1.24s Frontdesk VIP arrival 3pm, Mr Chen. Briefed the desk with preferences. Review 3-star on the check-in wait. Response drafted. ### Ask anything, on your own data. One question, checked across revenue, payroll, guest and ops, answered in seconds. ### Automate the manual reporting. Pickup, pacing, daily sales, payroll. Built once, delivered before you sit down. October 2026 Today OTB 62 % 74 % STLY −12 ### Agents that watch while you sleep. Give one a job in plain English. It only speaks when something needs you. ### Every answer shows its working. Nothing is a black box. Every number traces back to the system it came from. Case study · O'Callaghan Collection ## The Alex went from reactive pricing to about 120 rate actions a month. A four-property group across Dublin and London. One Flow reviews the forward calendar overnight. +8.6% RevPAR Growth vs. same period last year 110.4 RevPAR Index outperforming the compset +5.0% Above Budget combined Jan-Feb room revenue ~120/mo Rate Actions via Flows, every month “ I can't personally check every hotel every day but Otel gives me comfort that I can always see where the opportunities are, where the risks are, and that the team is actually acting on them. ” Joanne McDonnell Group Director of Revenue O'Callaghan Collection 120 rate actions a month. Same team, same system, one Flow. Book a demo Read the full story Who it's for ## Pick your morning. One view your whole team can stand behind, doing a different job for each. Owners & MDs Portfolio and margin Every property, ahead. The whole group in one picture you can believe, and the margin leak caught while there's still time to act. Every property, one view Margin drift flagged in the week it starts The same numbers your GMs are working from Group performance without waiting for month end Book a demo General Managers The property, day to day Walk in ahead. Every day. The whole hotel in view, problems caught while they're small, and room for the calls that need your judgment. The brief before you get in Every department, one place Tonight's arrivals, VIPs and gaps, before the shift The problems worth your morning, not all of them Book a demo Revenue & Commercial Rate and demand First to know. First to move. Every pricing move worth making. Drafted, with the working shown, and waiting on your yes. Underpriced dates, with the rate to move to The working behind every number Compset moves caught overnight Nothing goes live without your yes Read more Book a demo Finance & Back Office Cost and control The whole hotel, accounted for. Costs watched as closely as revenue, and the quiet drift caught before it compounds. Payroll drift by department Orders that never hit the approved list Cost per occupied room, tracked nightly The variance explained, not just flagged Book a demo Craft, built in ## It knows the work on day one, and your hotel from the first night. An RMS learns by watching your bookings for a year. Otel reads your history the first night. ### Years of craft, built in Trained on the job beside the people who do it, never on your data. ### Your history, remembered Reads years of your own trading on night one, and keeps every snapshot after. ### Your context, encoded Your rates, your segments, who you compete with, and the renovation that breaks the comparison. That's the difference between an analyst that's done the job and a chatbot you upload your files to. SECURITY ## Your team is already using AI. Just not safely. Right now someone is pasting a rate sheet, a guest list, a payroll export or last month's P&L into a public chatbot. Otel gives them the same speed inside a certified environment, on your own hotel's data. Visit our Trust Centre → ISO 27001 Certified The international standard for information security management. GDPR Compliant Your hotel's data is handled to GDPR requirements, and the practices behind that are reviewed and maintained. SOC 2 Type II An independent auditor checked our security controls over months, not on a single day. Details on our Trust Centre . Case study · Fitzpatrick Castle ## A four-tab morning routine, replaced by a report that writes itself. 113 rooms in Killiney. The pickup report now runs at 8am, broken down by segment, and the weekly forecast is ready before the meeting starts. 40 mins Daily sales report now automated Half a day Weekly forecast prep now ready before the meeting 8am Pickup by segment movement flagged by month 113 Rooms, Killiney an early design partner “ If I had to manually pull this from reports and present it, it might take me three weeks of work to get this kind of detail. ” Mark Scott-Lennon Managing Director Fitzpatrick Castle Hotel A four-tab morning routine, replaced by a report that writes itself. Book a demo Fitzpatrick Castle's story ## As seen in • • • • • --- ## For revenue teams URL: https://www.otelai.com/revenue For revenue teams # Price ahead of the market. Not after it. Your day starts at the decision. Book a demo → Chat ## Ask Otel anything What are the top most important insights you can give me about the business? Grendon Castle Opus 5 High How does pickup compare to last year? What needs my attention today? How are we pacing this month? What's net revenue after commission? Where are we behind budget? Results ## Measured in hotels running Otel. See more customer stories ↗ +8.6% RevPAR growth, against the same period last year 110.4 RevPAR index, ahead of the comp set +5.0% Above budget, combined Jan-Feb room revenue ~120/mo Rate actions taken through Flows While the hotel sleeps ## One night on your book. Nine catches, hour by hour. By morning it's one list: what happened, what it's worth, and what to do next. A composite night, but every catch is real and every line traces to source. Book a demo 11 PM 12 AM 1 AM 2 AM 3 AM 4 AM 5 AM 6 AM 7 AM 11 PM Audited new bookings 3 flags 23:40 61 new bookings checked. One at a €0 rate, one rate code not posting breakfast. Re-shopped the comp set Yield now 00:45 The market moved +€30 for Saturday. You didn't, at 92% sold. Raise drafted. Audited restrictions Release drafted 01:45 A November weekend isn't picking up direct. A stale 2-night minimum, still on. Shopped from the guest's side 44 rooms found 02:50 Booking.com says sold out. Your PMS holds 44 rooms. Fix drafted. Ran curves against budget Plan drafted 03:50 December is pacing behind last year. Segment targets and campaigns drafted. Checked group blocks €15k surfaced 04:55 One block holds 102 room-nights at €0, invisible to your forecast. Reviewed no-shows €438 caught 05:55 One had a card on file and no charge posted: €438. Prepped arrivals Team prepped 06:55 Two VIPs missing traces, filled from history. Upsell list built, prices attached. Wrote the morning report Your call 07:55 Full commercial report in every inbox, drafted moves on top. “ It sends me a report every morning: what to hold, when to yield, when to push. If a date is flagged below market, I go straight into my RMS and push the rate. ” Ela Szkamruk Revenue Manager, Fitzpatrick Castle Hotel Nothing goes live without you ## Every move arrives drafted, with its reasoning. Approve it, adjust the number, or decline and tell it why. It learns your call either way. Tuesday 13 October Awaiting your yes €189 € 214 +€ 25 86% sold, +9 rooms in 7 days , ADR -€12 vs last year, and the RMS hasn't moved it. Approve Adjust Decline Approve and it goes to your team, logged with the reasoning behind it. Your number goes out instead, with the working still attached. Declining asks why, and it learns your call either way. Edit pricing ✕ Floor & ceiling € 170 - € 240 €150 €280 Selected BAR € 214 Floor Mid Ceiling Add reasoning to improve AI recommendations (optional) Cancel Update pricing What stays yours ## Four things that stay yours. Rates ### Every rate move waits for your yes. Otel hunts, audits, builds the case and drafts the move, then waits. Auto-apply is a switch only you can flip. Team ### Your team keeps the judgment. The grind goes, the judgment stays. You stop digging and start deciding. Trust ### Every figure shows its working. Click any figure for the source system, query and timestamp behind it. Stack ### It sits on top of what you already run. Otel reads the systems you already run as one hotel, and hands the decisions back. Proof · O'Callaghan Collection ## The Alex went from reactive pricing to ~120 rate actions a month. The biggest ADR gains landed on Wednesdays and Thursdays, the mid-week dates that usually go overlooked. Read the full case study +8.6% RevPAR growth vs. the same period last year 110.4 RevPAR index outperforming the comp set +5.0% Above budget combined Jan-Feb room revenue ~120/mo Rate actions via Flows, every month “ I can't personally check every hotel every day, but Otel AI gives me comfort that I can always see where the opportunities are, where the risks are, and that the team is actually acting on them. ” Joanne McDonnell Group Director of Revenue O'Callaghan Collection Graded every week ## See how often we're right, and when we're not. A tool that only shows its wins is selling you something. Every figure is computed, not generated : click it and you get the query and the timestamp. So we can do the one thing a black box never will. The accuracy, published weekly Every week Otel publishes the watch's accuracy: the flags your team confirmed, the ones they declined, and the calls it got wrong. And the misses, shown, not hidden 24 logged · 2 open Fixed · 21 May CORR-024 ### Block feed freshness Opera block feed stopped updating on 14 May. Stale rows passed every check, so two lost groups still read as live pipeline. Feeds now prove freshness before a number is used. Fixed · 3 Jun CORR-031 ### Undercut alerts without inventory Undercut flags fired on dates already sold out. Correct, and useless: there was nothing left to sell. Undercut checks now require open inventory. Two recent examples. The full rolling log lives in the product. One layer over your stack ## It connects to the systems you already run. Even the ones with no API. Otel reads them all as one hotel, and remembers what it learns. ### Pre-built connections Opera, Guestline, Hotsoft, Apaleo, Mews, IDeaS, Duetto, Right Revenue, Lighthouse, STR, CoStar and more. ### Direct APIs Real-time, authenticated and audit-logged wherever your vendors support them. ### Computer-use agents For everything else, Otel connects the way your staff does, by seeing the screen and using the system. ISO 27001 certified GDPR compliant EU-hosted, ring-fenced per hotel Never used to train models One watch across every system ## Your systems each watch one thing. Otel watches all of them. The RMS prices, the rate shopper shops, and nobody connects them. Otel takes that job. October 2026 On the books 62% vs 74% STLY −12% Your rate €245 vs €227 compset +€18 August 2026 On the books 94% vs 91% STLY +3% Your rate €268 vs €259 compset +€9 September 2026 On the books 79% vs 83% STLY −4% Your rate €251 vs €246 compset +€5 October 2026 On the books 62% vs 74% STLY −12% Your rate €245 vs €227 compset +€18 November 2026 On the books 45% vs 48% STLY −3% Your rate €219 vs €215 compset +€4 December 2026 On the books 40% vs 37% STLY +3% Your rate €258 vs €249 compset +€9 January 2027 On the books 14% vs 15% STLY −1% Your rate €189 vs €192 compset −€3 February 2027 On the books 9% vs 8% STLY +1% Your rate €196 vs €194 compset +€2 March 2027 On the books 7% vs 8% STLY −1% Your rate €205 vs €201 compset +€4 April 2027 On the books 6% vs 5% STLY +1% Your rate €224 vs €218 compset +€6 May 2027 On the books 5% vs 6% STLY −1% Your rate €239 vs €233 compset +€6 June 2027 On the books 4% vs 3% STLY +1% Your rate €252 vs €244 compset +€8 July 2027 On the books 3% vs 4% STLY −1% Your rate €271 vs €258 compset +€13 August 2027 On the books 2% vs 2% STLY 0% Your rate €279 vs €262 compset +€17 Pricing & pacing Booking curves on every date, 365 days out, with the underpriced ones flagged and a rate suggested. Catching what used to slip Five jobs, one watch, all pointed at the revenue leaving while no one's looking. Every reservation, audited Yesterday's bookings checked line by line: comped rooms, wrong rate codes, suspicious multiples. Cancellations & no-shows Every no-show checked for its charge, and cancellation spikes caught the day they happen. Groups, watched closely Every block tracked on pickup against allocation, including the unrated ones your forecast can't see. The market & your competitors Named competitors on every rate move, and your pickup measured against theirs. Every system watched, every night. Book a demo Your context layer ## It knows revenue on day one, and your hotel from the first night. An RMS learns by watching your bookings for a year. Otel reads your history the first night. ### Years of craft, built in Trained on the job beside real revenue directors, never on your data. ### Your history, remembered Reads years of your pacing on night one, and keeps every snapshot after. ### Your context, encoded Your rate codes, segments, comp set, and the renovation that breaks the comparison. The first answer it gives you already speaks your rate codes and your comp set. Ask it for more ## Anyone on your team can hand it work. Your team gives it tasks in plain English, and picks where the answer lands. Run my pickup report at 8am. Scheduled, commentary written. Alert me on a cancellation spike. Silence means all clear. Build a pace-by-segment dashboard. Live in minutes, edited by chat. Who's upgraded to a lodge and not paying for it? Answered in two minutes. Delivered to where you work Outlook Gmail WhatsApp Slack Teams Excel We were in those meetings and a question was asked, there was a weak ADR in one of the months. It's like going to ChatGPT and saying give me all the group blocks for July, what's dragging down the rate. It comes back in about ten seconds and tells you exactly where your problem is. I asked it to pull anyone upgraded to a lodge who isn't paying for it, something that would have taken the res team ages going through individual bookings took me two minutes. I created a flow today for the report I build manually every week: budget versus on-the-books, plus last week's pickup. Forty minutes, every week, and I don't have to do it anymore. Seán Reid Group Commercial Director The Johnstown Estate Melissa Noone Revenue Manager The Johnstown Estate Sharon Begley Revenue Manager Pembroke Hotel Kilkenny ← → For the whole group ## Oversight without another meeting, one hotel or the whole group. It stays quiet while everything's on budget, so you walk into Monday already across the numbers. Grendon Castle Dublin Healthy Grendon House London Healthy Grendon Quay Manchester Healthy Grendon Court Cork Healthy Grendon Park New York Attention Needed 50-room block, 0% picked up, 33 days out ## The questions you're already asking. ### Is this an RMS? + − No. Your RMS prices, Otel watches what it misses: the un-yielded event, the stale restriction, the forgotten floor. No RMS? Then Otel watches your book directly. ### Will it move our rates? + − Only when you say so. Every move arrives drafted with its reasoning, and auto-apply is a switch you control. ### Why not just ChatGPT? + − A rented model knows the world. Otel knows your codes, your history and your comp set, with every figure computed by locked queries rather than generated. ### What happens on the walkthrough? + − You bring one date range that's been bothering you, we connect a read-only view of the systems you already run, and Otel works that window while you watch. You keep the findings either way. ### Our owners keep asking what we're doing with AI. + − Point them at the watch: the money found, the moves drafted, and a person approving every change. It's an answer a board can trust, because every number shows its source. --- ## Customer stories URL: https://www.otelai.com/customer-stories Customer stories # Real hotels. Real outcomes. How operators are using Otel to walk into decisions, not data. Trusted by hotel operators Case Study · O'Callaghan Collection ## The Alex went from reactive pricing to 120 rate actions a month. Same team. Same systems. A four-property hotel group across Dublin and London. The revenue team knew where the gaps were. They just couldn't act on every date, every day. One Flow changed that: review the full forward calendar overnight, flag underpriced dates versus comp set, and have recommendations ready before the first cup of coffee. Read the full story +8.6% RevPAR Growth vs. same period last year 110.4 RevPAR Index outperforming the compset +5.0% Above Budget combined Jan–Feb room revenue ~120/mo Rate Actions via Flows, every month “ I can't personally check every hotel every day but Otel AI gives me comfort that I can always see where the opportunities are, where the risks are, and that the team is actually acting on them. ” Joanne McDonnell Group Director of Revenue O'Callaghan Collection Case Study · Fitzpatrick Castle Hotel ## How Fitzpatrick Castle's MD swapped a four-tab morning routine for an AI co-worker. 113 rooms in Killiney, Co. Dublin. Mark's morning used to mean Guestline, Lighthouse, payroll and a pickup report, cross-referenced by hand before a single decision got made. Now the pickup report runs itself at 8am, broken down by segment, and the weekly forecast is ready before the meeting starts. Read the full story 40 mins Daily sales report now automated, every morning Half a day Weekly forecast prep now ready before the meeting 8am Pickup, by segment flagging movement by month 113 rooms Killiney, Co. Dublin an early design partner “ It's like having a mixture of a P.A. and a data analysis person. Reducing the mental load that I have day-to-day, that's where I've loved the Flows. ” Mark Scott-Lennon Managing Director Fitzpatrick Castle Hotel --- ## HITEC 2026 URL: https://www.otelai.com/hitec We were at HITEC 2026 # Your whole hotel, in one mind. We were at HITEC 2026 this June. Missed us on the floor? Book a demo and see Otel live instead. Book a demo See The Alex case study Results from hotels running Otel 20+ hrs/week Back from manual reporting and analysis 100+ Connections System integrations 10× monthly Pricing decisions 8.6% in 3 months RevPAR uplift ## Same team. Same systems. Ten times the output. Your team already knows what to do. They just don't have the hours to do it all. Otel handles the analysis, the monitoring and the manual work, across every department, so the work is done before your team sits down. Book a demo ### Every System Connected Live pulls from your PMS, RMS, payroll, F&B and comp set. Real context across your whole stack. Today with Otel 10× Output Same team. Same systems. ### Overnight and weekends The reports are built while you're closed, ready before you sit down. ### 6 Departments Revenue · F&B · Payroll · Operations · Procurement · Guest Reviews ## Agents that act with full context behind every move. Book a demo Manual work ### The repetitive work, handled Pickup reports, pricing analysis, payroll reviews, daily sales, arrival prep: the work that eats your morning, built and delivered before you sit down. You set it up once; it runs every day. Always watching ### Agents that act on their own Some problems you don't know to ask about. Otel watches every system and surfaces them on its own: a soft date with restrictions still on, a complaint theme repeating across reviews, payroll creeping up in one department, a purchase order to a supplier that isn't on your list. You're not relying on someone to spot it. Knows Your Hotel ### The brain behind every agent The shared memory underneath every agent, and its memory of your hotel specifically. Your rate strategy, who you compete with and where you like to sit against them, the suppliers you actually use, the year you were closed for renovation. Generic AI knows what a hotel is. Otel knows yours. Case Study · O'Callaghan Collection ## The Alex went from reactive pricing to 120 rate actions a month. Same team. Same systems. A four-property hotel group across Dublin and London. The revenue team knew where the gaps were. They just couldn't act on every date, every day. One Flow changed that: review the full forward calendar overnight, flag underpriced dates versus comp set, and have recommendations ready before the first cup of coffee. +8.6% RevPAR Growth vs. same period last year 110.4 RevPAR Index outperforming the compset +5.0% Above Budget combined Jan–Feb room revenue ~120/mo Rate Actions via Flows, every month “ I can't personally check every hotel every day but Otel AI gives me comfort that I can always see where the opportunities are, where the risks are, and that the team is actually acting on them. ” Joanne McDonnell Group Director of Revenue O'Callaghan Collection 120 rate actions a month. Same team, same system, one Flow. Book a demo Watch the case study ## The operational layer your hotel runs on. Built around how hotel teams already work. ### One operational layer Direct connections to PMS, RMS, F&B and payroll. Not dashboards bolted on top. The actual systems you run on. ### Live, not last-night Real-time state across every system. Nothing waits for the overnight sync. ### Cross-department by default Actions span revenue, operations, F&B and front desk. The handoffs happen on their own. ### Audit-grade transparency Every recommendation shows its work. Click any decision to see which system was read and why the call landed where it did. Nothing's hidden behind the model. ### Built for portfolio scale Multi-property out of the box. Drill into one hotel or compare across the group. ### Built with operators Operators shape what we build next. Every line on the roadmap traces back to a hotel that asked for it. Integrations ## Connect the tools you already use Your stack stays exactly as it is. We read it, reconcile it, and surface what matters. The morning brief lands wherever your team already works. And 100+ more hotel systems. Don't see yours? We'll connect it. --- ## The Otel letter (newsletter) URL: https://www.otelai.com/newsletter # The Otel letter Once a month. What hoteliers actually built with Otel, what we shipped, and a few things worth reading. No product announcements dressed up as insight. Email address Subscribe ---