Ness made waves when it launched its personalized restaurant search and discovery app – GigaOm likened the service to a ‘Pandora for restaurant recommendations’ – and is now going to use the proceeds of the financing round to further improve its search technology and bring it to new verticals like movies, event, shopping, nightlife and whatnot.
Ness’s search technology is referred to by the company as a “Likeness Engine” that essentially curates personalized recommendations across various categories based on their tastes and preferences.
At the same time, Ness is careful to continue updating its flagship iPhone app ‘Ness Dining Guide’, which has been updated with a bunch of fresh features.
The startup’s so-called “Likeness Score” predicts how much a customer will like a restaurant based on their unique preferences, making it easier to find a place they’ll enjoy. The company’s technology takes into account “social signals” from services like Facebook, Instagram and Foursquare.
Ness claims its users have already generated over 2.5 million ratings, and the app includes a baffling 5 million Instagram images (and counting) for restaurants.
The capital will also be used to expand Ness’ team of engineers and computer scientists in systems and interface engineering, as well as machine learning, an essential part of what makes the company’s search technology worth a second or third look.
Ness has raised $20 million to date. Its $5 million Series A round of financing was led by Vinod Khosla and Ramy Adeeb of Khosla Ventures with participation from Alsop Louie Partners, Eric Schmidt’s TomorrowVentures, Bullpen Capital, a co-founder of Palantir Technologies and several angel investors.