Empire State Building
Introduction
The work with the Empire State Building began with a focused request: build an intelligent AI chatbot that could help visitors choose and buy the right ticket. The assistant understood the ticket catalogue, interpreted free-form questions, recommended the most relevant experience, and guided each visitor toward purchase.
Challenges
Turning a conversation into the right ticket
The first challenge was product knowledge. The assistant needed to understand ticket types, prices, access levels, time options, upgrades, and restrictions, then turn a visitor’s text description — who they were travelling with, what they wanted to see, and how flexible their schedule was — into a clear recommendation.
AI ticket advisor
From a visitor’s question to the right ticket
The chatbot was trained around the real ticket catalogue rather than generic support content. Visitors could describe the experience they wanted in their own words, and the assistant used ticket access, timing, flexibility, upgrades, and audience needs to recommend the most suitable option and explain why it fit.
Ventrata integration
Connecting recommendation to purchase
The recommendation only became useful when it could lead into a real booking. I integrated the experience with Ventrata, adapted its data and availability model to the interface, and customised the flow so visitors could move from the suggested ticket into a clear, responsive purchase journey.
Final thoughts
An AI ticket advisor connected to a production booking flow.
Visitors could describe the experience they wanted in natural language, receive a relevant ticket recommendation, and continue into a customised Ventrata purchase journey without having to decode the catalogue themselves.
