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I am working on Blubyn - an AI powered travel agent helping users book flights and hotels quickly by personalizing results. Here is the link: http://onelink.to/blubyn (app only - available on both iOS and Android)

Being an avid traveler, it has always bothered me that travel experience has remained almost the same over the years. We scout 50 websites to figure out where to go and what to do, where results/posts are something written with a view of catering to everyone(and hence very little for my interests), then to book I have to look at 100 different variables (and repeat the process almost everytime), and not helped by 8-10 websites which all look and function the same way - showing the most results, and not being upfront about anything. It still takes me half an hour to book a flight or hotel - when I do the same set of checks and actions everytime.

Once the booking is done, now again begins the anxiety of scouting trip advisor and lonely planet and forums to get more knowledge about a place. Altogether its a very inefficient experience, to say the least. Comparing that to buying a product on Amazon, one click booking, personalization, one stop shop, a seamless experience, and its fares really bad.

We want to bring that Amazon experience to travel. We have just started, long way to go. Hoping to crack it.



Lots of people tried to tackle this problem before, what's your unique take on it?


A lot of solutions focused on building itineraries, and to me that is where they missed the mark. Planning and itinerary building is not a hassle, its part of the experience. People like an itinerary made for them, but they dont follow it, cos it feels like work routine. The hassle part is the struggle in finding the relevant information. All the blogs try to cater to everyone and hence arent that relevant for one person (results and articles arent personalized). Then the information is way too scattered so it takes time finding it. Third, most blogs and articles are written from conversion viewpoint so that decreases the reliability. We can solve all three.


Interesting. Which GDS are you integrating with in the background or are you using something like Skyscanner? How do you guarantee you are giving users the best price?


Right now, its just Skyscanner and a couple of other vendors. We let go of our margin to ensure the lowest prices.


Could you elaborate on the "AI" part of it?


Sorry, saw this late.

There are a few AI components here:

1. ML based recommendation engine to suggest flights, hotels, activities/experiences, and even destinations based on profile (social data, interaction data, and booking data) and clusters based on certain components. (Currently works well for flights at 85% accuracy - top five results, for hotels, we are at 52% in top 10 results)

2/ Voice + NLP engine to handle more intuitive queries. One aspect of travel inspiration is that when people google, they dont ask the question they have. Like for a question like 'Where can I go for a beach trip next weekend' becomes a search query of 'Top beaches in US' or 'Top 10 exotic beaches'.

3/ 80% of the trip planning effort is spent on just finding the relevant info cos it is way too scattered. There is a way it can be made more concentrated, when we scrape more data from existing blogs, and create a graph network of information to serve a more relevant and contextual answer to the queries. Initial thoughts only on this, since we are still solving this. (Example would be, let's say you are planning a trip to Thailand, the product should be able to give contextual info keeping your preferences in mind. If you are an adventure lover, focus would only be on those activities, if you like a secluded beach to relax, you will be given those answers.)

3rd is the most complex and requires a lot more effort. This is not the same as itinerary building (cos that is the part of experience). We just want to take away the frustrating bits away from the planning part.

Apart from these, the usual features, like fare prediction, flight delay prediction, deals info, are also on the roadmap.




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