SILICON VALLEY, Calif., April 17, 2013 /PRNewswire/ -- Ness Computing today released Ness 2.0, debuting a brand new and beautifully designed interface with a number of exciting new features. The personalized restaurant recommendation app, available exclusively for iPhone and iPod touch, anticipates your dining needs and presents elegant, swipeable recommendation cards that summarize the information you need to quickly find a restaurant you will love. Like Pandora does for music, Ness adapts to your tastes to provide instant recommendations for you, not the crowd.
Ness' new restaurant recommendation cards display enticing images to give an immediate sense of each restaurant; your personal Likeness Score to show how much Ness predicts you will like a place; and an explanation for why Ness is making the recommendation. With quick swipes, you can easily scan the best options and find a great place to go to now, or to save for later.
Ness adapts not only to your individual tastes, but also your situation, allowing you to quickly adjust what, when and where you are looking to eat. Since the app is smart enough to distinguish between places that are especially great for specific meals—like brunch or late-night dining—Ness intelligently responds to what you're looking for.
"We're dedicated to building a service that is deeply personal and intuitive. Different people have different tastes, so Ness makes unique recommendations for each customer—and each situation —rather than providing the same results for everyone in every situation," said CEO and co-founder Corey Reese. "With Ness 2.0, we've built a product that anticipates what you're looking for, then offers the fastest and easiest way to find restaurants tailored to your tastes. Instead of relying on reviews from strangers, Ness is all about you."
Ness is available for free from the the App Store on iPhone and iPod touch at www.appstore.com/ness
About Ness Computing
Ness Computing's mission is to connect people with experiences they'll love. The company uses advanced machine learning techniques to recognize patterns in people's preferences, and their first product makes instant restaurant recommendations based on each customer's unique tastes. Ness Computing's team has expertise in applied machine learning, natural language processing, collaborative filtering, large-scale systems, and mobile user interface engineering. Ness is based in Silicon Valley. For more information, please visit www.likeness.com.
SOURCE Ness Computing