Customer Story

How Fitzpatrick Castle’s MD swapped a four-tab morning routine for an AI co-worker, and built a 15-room expansion case in 30 minutes.

The challenge: scattered data, time wasted, opportunities missed.

Every morning, Mark arrived to a familiar ritual. Log into Guestline. Pull the pickup report. Open Lighthouse. Cross-reference what the RMS was surfacing. Check payroll variance in Alchemy. Build a picture, manually, across multiple tabs, before a single decision had been made.

The reports existed. The data existed. What didn’t was a way to see it all in one place, interrogate it in the moment, and act on it before the day ran away.

The shift: from static reports to live conversations.

Fitzpatrick Castle joined Otel AI as one of its earliest design partners. Mark was sceptical about Flows at first. Then he started using them.

Within weeks, he had a pickup report that ran automatically at 8am, broken down by segment, flagging movement by month, and showing him his seven-day pickup on demand. When something wasn’t right, or when more detail was needed, he went back into the chat and changed it.

A 15-room expansion, modelled in 30 minutes.

The case for adding 15 new rooms needed to be built. Mark spent 30 minutes with Otel AI, starting with the projected revenue contribution based on Fitzpatrick’s actual 2025 performance, by month, by segment, and accounting for group business carrying April through October while high-occupancy shoulder nights picked up the rest.

Otel built the model. An Excel with monthly projections, incremental cost assumptions, payback period, and a contribution-to-profit summary. Then it offered to build him an investor-ready deck.

What’s changed since.

Weekly forecasting now arrives as a structured report, ready before the meeting starts, adaptable in real time.

OTA share versus direct bookings is tracked on a rolling basis. Comp set rate movements get flagged automatically. Payroll variance arrives mid-week, not at the Friday post-mortem.

The GM morning brief flags suite availability against arrival volume, prompting the right call to front desk at the right time. Not a dashboard to check. An action to take.

What Mark notices most.

Mark is methodical about what works and what doesn’t. When something’s off, he flags it. When something surprises him, he pays attention.

What surprised him most wasn’t a single feature. It was being able to ask his own data a question, in plain English, in the middle of a meeting, and get a real answer there and then.

Even if I’m in a meeting and there’s something specific we’re talking about, I can go into the chat and ask something like “Can you tell me how many rooms X company did this month versus this month last year”, and I can immediately have that information.

He also observed that hotel teams don’t need to be technical to get value. GMs, revenue managers and operations can start with Templates (Otel’s ready-made Flows) and get value from day one, then build their own Flows at their own pace.

For people who are a bit slower technologically, they’re at least getting base-level value by using the templates. And then people more okay with technology can get further value by interacting with it.