Relaunches Its Foodspotting Competitor To Make “Best Dish” Recommendations Using Reviews From Yelp, Foursquare And Instagram is a new restaurant recommendation mobile application, launching today, which focuses on helping users find the best dishes at their local eateries. Initially, the company had gone the Foodspotting route, debuting an early version of the app this summer which relied on crowd-sourcing techniques to fill its database with photos and reviews. But just a month after the app went live in the App Store, the company knew it had to revamp. Today’s app scraps that earlier approach, and now generates its “best dish” recommendations using sentiment analysis technology, not original user-generated content.

The interesting thing about’s approach, is that it’s building on top of the content shared on established websites, including Yelp, Foursquare and Instagram. To help determine which dish is the best at a given location, the startup is analyzing the public reviews and tips found across the web, and then extracting positive reviews from the various services. Each positive review is counted as one “like” within’s app.

dishfm-2Finding the best picture to accompany the top dishes also involves a technical analysis – this time, counting how many likes the photo has, as well as how many people are following the user on that social service.

According to co-founder Zhanna Sharipova, who started the company around a year ago with longtime friends, Dilyara Mingalieva and Andrey Surin, the idea is to combat the problem of reduced engagement with market leaders in the food recommendation space, like Foodspotting. “We asked users, why are you not using Foodspotting every week or every day? And the answer was constantly the same: there’s not enough content there…I can’t get enough quality recommendations.” Users told’s founders that the ideal service would work in any restaurant and have at least ten dishes to choose from with at least ten votes apiece. That way it feels trustworthy, Sharipova explains. Otherwise, the recommendations seem random. “One or two people can be mistaken,” she says.

But Foodspotting and other user review sites like Yelp and TripAdvisor have taken years to get where they are today. “We asked ourselves, ‘is there a way to do it tomorrow?'” That’s where the idea came from to build on top of the data that’s already available, and try to make better sense of it. And most importantly, the goal with is to make it simple to quickly access those learnings in order to better answer the question “what’s good here?”

In the app, you can tap on any item to view the photo larger, read the description, and tap on a button to tell others you liked it with just one click. “Taking a picture, writing a review and giving it stars requires too much effort for people,” Sharipova says. is meant to be quicker and easier to use.

The new application, live now in the Apple App Store, only supports New York and San Francisco at present, and offers around 100,000 photos, and dish recommendations based on 3 million reviews. The company plans to grow to other U.S. markets in the coming weeks, including L.A., Chicago and Boston in the near-term. The goal is to scale up to 100 million reviews by the first half of 2013. is based in Moscow, but Sharipova travels between Moscow and San Francisco. The company plans to establish an office for the commercial team, sales and marketing in San Francisco, but keep development in Moscow in order to access the high-quality, but cost-effective, local talent. is backed by Igor Matsanyuk‘s, which invested $300,000 in the company. The startup is not currently monetized.