Having spent three years in development, news aggregator Wavii launched in beta today. The service attempts to organise web information and news in the same way that Facebook organises information about your friends.
A timeline of posts
Wavii (pronounced wavey) provides users with a timeline of posts in much the same way as Facebook. On registration you select specific topics of interest, from the four main categories of entertainment, technology, business and politics. For example, I selected Google, Facebook, Microsoft and other big names in tech to get all the news on the tech industry. I was returned with a timeline full of stories featuring these companies.
What separates it from Google Reader or other aggregators is that Wavii doesn’t just return article headlines or introductory paragraphs; it searches the text to find sections that it thinks are of interest to me, and can create a story from multiple stories. The timeline generally contains a headline and an image or quote and if you click into a story you get a little more detail. Content is pulled from news sites, blogs and even Twitter and Facebook posts. Links are provided to the original sources if you want more detail.
Wavii welcome page
Tough to gain traction
Wavii has brought together a 25-person staff full of big data and machine learning experts, many of them alums from Amazon and Microsoft, and 29 year-old CEO Adrian Aoun says that the company has patents filed around the technology that makes its product possible.
Aoun’s service is available on the web or through an iOS app and you sign in via your Facebook account.
The biggest challenge for the Seattle based Wavii is that it is not providing a startling new service. People have already formed habits around consuming their news, whether it’s from Google Reader, or Facebook or the BBC and whilst Wavii’s service may be better, gaining traction in such a busy market could prove difficult.
Aoun says that there is no revenue model as of yet but mentioned that advertisers may be interested in providing ads to users based on their interests, as they do on Facebook.
