Ricardo Grego

We now trust online and digital reviews and recommendations systems to support and guide most of our decisions, from choosing a new restaurant, buying a new product or finding a good doctor. These systems use complex algorithms to analyze huge amounts of data and return the “best” results based on metrics such as page views, stars, like buttons, date and other criteria that are frequently not clear for us.

However these systems frequently do no not reflect the way we exchange information and discover things offline. Instead of asking for the opinion of a crowd of strangers, we usually ask for the opinion of our friends, or even just one of them. That’s because our friend’s opinions are much more reliable and personalized according to known experiences and interests.

The growth of digital social networks and communication platforms such as Facebook and Twitter has made it possible to exchange information in real-time with our friends. However the real-time dynamics makes the information created be lost and almost possible to search and/or organized in a way that it can be reused.

Modeled after offline users behaviors, BuddySight is a social recommendation engine powered by users’ network of friends. that facilitates the exchange of recommendations of great local business and services, such as restaurants, stores, lawyers, doctors, mechanics and more within our social networks.

BuddySight is a website and mobile application that allows users to request or give location-based recommendations to their friends creating a direct channel to exchange and access the favorite businesses and services according to your friends opinion, helping to find and promote the reliable and great businesses that we trust.