Hot application Frilp from India, let a friend’s recommendation to help you find everything

on May 21, hunting cloud network

if you want to find a nearby place go to a yoga class, what would you do? You will search online or on classification web site look, check the score on the comments on websites. Time is ok for you? The coach of everyone’s attention? The environment? Want to know that you have more homework to do.

your request more specific, the more difficult it is to find you want, for example, if you want to find a excellent dental root canal surgery technology, or a local Indian food is very delicious restaurant, food can’t be too too spicy oil, or a small pub, beer is very fresh, the atmosphere is not too loud, can quietly watch a cricket match. So in this case, you would ask your friend.

but do you know how do you know which friend is a yoga class or tavern? The ideal situation is that people have been to these places, so you start to ask around, on Facebook or WhatsApp questions, if you’re lucky, one of your friends will give you a good advice. But it really is not an efficient solution to the problem.

if a website can let you in their own social circle search want what do you think? It can according to your need for intelligent query, will be sent to your friends and family, and get the answer from the right people, and the answers will be stored in the network of the questioner, when having a similar problem can also see you next time.

is difficult to solve the technical problems of

India sites Frilp can let your friends to help you, it USES advanced algorithms, based on your social network, and the recommendation of friends and family in the mobile phone contact, recommend to you the store or service. Frilp COO and co-founder Senthil K explain to us why this is a hard to chew bones: “we will be according to your data, combined with the presenter’s working place, working content and behavior on social media and other data, first pick out those you lifestyle or work conditions similar answers. The data which we call “credibility”, and use it to predict someone is your friends or colleagues, even if you don’t have these special statement.”

those who would be in Zomato or TripAdvisor websites people write reviews for products or services account for only a very small part, we generally do not give the kitchen decorate write a comment or root canal surgery, but we will respond to questions from friends, for they recommend a dentist or interior designer.

you ask questions after Frilp will ask your friend for an answer. Search engine is unable to answer a very subjective question.

we sat in the Arbor bangalore Brewing Company in the corner, open a tavern, where filled with from Microsoft Ventures Growth Program (Microsoft vc Growth plan) of technical personnel and entrepreneurs, including Frilp. In such an environment we discussed in search of what is one of the biggest challenges. As Senthil said: “Google can help you to find a dentist in jia yamaha, but it can’t tell you which dentist is the most popular with your friends.”

Stanford period in a flash of

Senthil K and Shyam Anandaraman both young entrepreneurs from Stanford university, they and the other three friend Raja Jayaraman, Anish Deenadayalan and Aravind Gopalan together established the Turing in chennai Research Labs (Turing Research laboratory, the laboratory in the second world war British decoding expert named Alan Turing, means they will also pass Frilp recommended mystery of “social”.

Girish Mathrubootham is one of the early supporters, he founded one of India’s most successful software companies Freshdesk. This month, the British company TechHub picked five fast-growing start-ups to Manchester to visit learning, Frilp among them.

Shyam Anandaraman before joining Senthil, have been Goldman Sachs on Wall Street (and Goldman Sachs). Together they education technology company, in the center of the chennai Global Scholar at work, for the first time recommended about social networking platform. “Shyam back to India, want to decorate the house, found it hard to buy all the things. Although there are JustDial but that there are only so many suppliers in the above, option is too small. We want to see how many people encountered such a problem, and then found the JustDial one month alone received 15 million questions.” Senthil recalls.

they at Stanford when researchers want to know the key places in the riddle.

“when something important happened, there was a visiting professor at Ashish Goel, he write a recommendation algorithm for Twitter. He saw we are doing, just he is also trying to solve the problem of network noise. We found that the consistency of issues of mutual concern, and he also like our algorithm. Since then he has cooperation with us, studies how to determine the identity of people, and puts forward the concept of credibility.” Senthil said.

the two young entrepreneurs took nearly four months in the silicon valley visited several bosses, including Twitter founder Jack Dorsey. “We did a lot of inspiration.” Senthil said. “they told us, for example, early adopters will be the tone of the whole platform, so we use for months for a closed beta testing to find out those that can give high quality recommended by the user, so that other users can on the basis of them.”

chennai and bangalore has many technical personnel are immigrants. Frilp founders often see someone asks what others where delicious, which have good problems such as a doctor, so after they come back from Stanford to look to the professionals who drift in bangalore and chennai.

“we picked out the five employees with the best quality of IT company, find out on Facebook or other social networking sites to respond to similar problems those most positive.” Senthil said, “we meet privately with the 500 people, try to figure out the problems after they came to bangalore and chennai, and from ever encountered greater difficulties has collected 3000 specific recommendations. Then we face these IT released our website, as the college students had Facebook begin, so people can see what their peers recommended.”

experts recommend for a rainy day

Frilp is now open to more people, the number of users has exceeded 100000, you can still see the reference information, Frilp are not anonymous.

as more and more users to join, a growing number of recommendations are stored, Frilp also develop better and better, but still can’t avoid, one day, the things you want to be your friend all don’t know. In order to solve this problem, Frilp will be based on user behavior on social media and Frilp to find some way of “experts”, for example, a version is likely to be more understanding of a local hotel.

“we will give you the answer you may push, if you have a good answer echo will take you as a specialist. Social identity and some shopkeepers for goods can bring a sense of achievement to experts.” Senthil said. So when the user’s friends can’t give recommendations by experts to fill the gap in a particular field. Experts can build a collection list, list the favorite goods, location, services

Australia application Posse used the similar pattern, also get recommendations from friends, as its website says: “found the world’s best restaurants, shops, hotels.”

from a business perspective, this kind of personalized recommendation than classification web site, review site more valuable or advertising. The most important is that it can save a lot of time. “If there are so many choices, you have to spend a lot of time to look up information. But if someone you trust to you recommend, you need not so trouble.” Senthil said, “as you want to decorate your house, you go to online search decorate a company, will get a long list, do you want to call consulting one by one, to look at them before decorate, still has a lot of other things to pay attention to, before you trust a selected, it’ll therefore take quite a long time. But if you have a friend and you taste similar, just to let a company to decorate the house, the effect is good, you can save a lot of time and energy. What we do is to make it possible to do such a thing.”

but if someone knows nothing but pretends to know or fraud? After all, this kind of thing often happens in real life. This problem laugh Senthil: “indeed, friends also may lie to you, this is not to rely on technology to solve.”

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