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Chatbot-Powered Travel AIs

Menzi Makes Travel Easier Through a Chatbot-Style AI System

— August 23, 2018 — Tech
American Express recently announced its acquisition of Mezi, an AI-based virtual travel assistant that allows users to book flights, hotels, and everything in between. Originally launched solely as an AI-powered virtual assistant, Mezi switched focus to travel in 2016. The app itself presents users with a messaging-style interface and functions as a chatbot. Users are then able to interact with the app by texting questions with the AI search and bring forward results based on what the user texts.

The decision to focus only on travel was decided when Mezi noticed requests grew three times faster than personal shopping.

Unlike other AI-based systems, Mezi doesn't use existing AI such as IBM Watson. Instead, the travel-focused AI functions on proprietary deep learning and natural language processing systems.
Trend Themes
1. Virtual Travel Assistants - Opportunity for AI-powered chatbot-style systems that assist users in booking travel arrangements, offering convenience and personalized recommendations.
2. Messaging-style Interfaces - Potential for chatbot-style interfaces that mimic messaging apps, providing a familiar and user-friendly experience for interacting with AI-powered travel assistants.
3. Proprietary Deep Learning AI - Disruptive potential for proprietary deep learning and natural language processing AI systems in the travel industry, offering improved accuracy and customization.
Industry Implications
1. Travel - Travel industry can benefit from integrating AI-powered virtual assistants to enhance customer experience, streamline bookings, and provide personalized recommendations.
2. Artificial Intelligence - Opportunity for AI technology providers to develop and offer specialized AI solutions for the travel industry, focusing on chatbot-style interfaces and deep learning algorithms.
3. Customer Service - Customer service industry can leverage AI-powered travel assistants to automate and enhance customer interactions, reducing response times and improving satisfaction.
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