Neither one was as comprehensive or up to date as they should be. Searches for news about major companies such as Google or Facebook missed headlines that other memetrackers such as Techmeme do a better job of capturing. But both have merits as prospective search tools and are examples of how search is increasingly becoming more of a navigational tool.

Evri’s Collections feature lets you “follow” any concept that the semantic search engine has categorized. The Collection page brings up not only recent articles, but also images and videos for the topic you are tracking. It also provides a handy list of related topics and concepts. For instance, my “Google” collection offers links on the side to “Eric Schmidt,” “Twitter,” “Microsoft,” and the lost city of “Atlantis.”

Evri’s collections pages are basically saved searches, with different entry points to navigate to other entries on Evri and across the Web. Topics can be merged in the same collection, so you can follow Google and Facebook on the same page. For some reason, Evri chose to show only the latest three articles for each topic, which is much too limited. It certainly doesn’t capture all the news you’d want to see. And if Evri’s semantic search engine has not categorized what you want to track, you are out of luck. For example, it doesn’t recognize the DEMO conference as a separate topic.

Ensembli, in contrast, provides a much simpler interface. Once you sign up, you type in the topic you want to track, and then Ensembli uses artificial intelligence software to generate a feed of articles about that keyword. The fed updates as new articles appear. You can follow as many topics as you want, but there is no way to browse topics or find related topics. You are presented with a blank search box and either know what you want to track or you don’t. Each headline can be expanded to provide a summary of the article, and you can share each headline, but only via e-mail.

When you click through to a story, you can also share it directly via an Esnembli toolbar at the top. (You are actually sent to an Ensembli link which frames the underlying Webpage, much in the same way Ginx and Digg’s upcoming toolbar present shared pages). Integration with Twitter, Facebook, Friendfeed, and other social sharing services is sorely lacking.

I have a few other issues with Ensembli as well. There is no way to combine topics into a single feed. You have to click on each term you are following to see the respective headlines. There is no way to see them all together. The biggest weakness, however, is that the headlines are not always as comprehensive or up to date as they should be. For instance, tracking “Google” turns up one article from yesterday as the most recent one, and then before that is an article from February 18. There are enough things going on at Google and enough coverage that Ensembli should be able to produce multiple headlines every day. Finally, Ensembli even had trouble identifying articles about itself. (I got a bunch of articles about “ensembles,” a forgivable error, but you’d think the startup would have at least properly categorized itself).

All in all, Evri wins this faceoff.

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Evri, a site that uses semantic searching to help users discover more Web content in the shortest amount of time, has added a number of new product features today to mark its open beta.

The site now features a content recommendation engine that publishers can add to their sites to let visitors browse Evri’s listings and profile pages where Evri will collect all the related content on a particular topic. In addition to videos, Evri also added an image carousel to its results pages, which it collects from across the Web.

The idea sounds fine — Evri wants to collect some of the best news, videos, photos, and important information from news sources, Wikipedia, and Google (to name a few) to create a more informative experience — but it falls flat on its face on too many levels.

Sure, it’s nice to have videos at my disposal on Evri’s page instead of searching for them on YouTube and it collects basic content from Wikipedia so I don’t have to surf my way around the Web, but most of the general information and news can be found on Wikipedia anyway. And while the images and videos are a plus, they are not enough to make me want to use Evri.

Not only that.  The site is missing a slew of simple topics and on a major topic like Android, it only has seven “top” relevant news articles. If I did a simple search on Google News, I’d be able to find thousands.

I took Evri for a spin to make sure my initial distaste for the service wasn’t made in haste. Unfortunately, it wasn’t.

I first started out with something simple by searching for “Android.” The site returned an informative page on Google’s software and included information it collected from Wikipedia, YouTube, and elsewhere. I was surprised that the site’s image results displayed just two screenshots of Android’s interface. The rest were images having nothing to do with the software—some stills from a 1960s movie, a man rock climbing, a random drawing, and some shots of the iPhone and Blackberry. I then surfed over to Wikipedia and searched for Android and gleaned much more information about it. And considering the videos and images were a bit off, I didn’t miss much at all.

What about a person search? Many of the same problems persisted. I tried something a bit more obscure than “Bill Gates” and searched for “Dean Martin.” Finally, the site returned relevant images and a bunch of videos that proved extremely relevant. Only this time, the news results were crazy: the top result mentioned Lehman Brothers and its financial woes.

What amazed me most about Evri was the sheer number of sites, people, and companies that it doesn’t support. Granted, it’s still in beta and its public launch was just today, but it’s missing startups like Yammer and FriendFeed and relatively well-known dog breeds like golden retriever or airedale terrier.

Finally, Evri’s “Top Connections” functionality is a bit suspect. Once you find the result you’re looking for, you can click on the connections it formulates for the term. In other words, if you’re searching for Microsoft, the site will show a diagram with Microsoft in the middle and a series of circles with company names in them connected to it. If you click on one of those circles (Yahoo, for one), it’ll display news articles pertaining to both Microsoft and Yahoo. Amazingly, those two companies only returned 10 top results — a ridiculously low number given their history.

Here’s what that looks like for “TechCrunch”:

Evri is trying to make the Web simpler for its users, which is probably why it doesn’t list so many news results and keeps the descriptions it collects from Wikipedia to a minimum. But because it chooses to do that, Evri quickly becomes a source for those who want quick access to videos and not much more. If you’re looking for in-depth knowledge about a given subject, Evri simply falls short of its aspirations.

And perhaps that’s why it was lost on me.  I can get all that information elsewhere and chances are, I’ll be able to find better information much faster.  If this is the best the Semantic Web has to offer, it still has along way to go.

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Evri, the site that uses semantic connections between terms to help users discover related information, has launched in private beta. You can register for an invite here.

Evri founder Neil Roseman (former VP of Technology at Amazon) is quick to explain that it is not a search engine. Rather, it helps users find related information by analyzing text to determine relationships between related terms. For example, a search for Barack Obama would likely yield a visual graph linking him to the Democratic Party, his wife, and other senators, along with a succinct summary of his background. Unlike the human-powered search engine Mahalo, Evri is powered by an algorithm.

The site made its debut appearance at last month’s D6 conference, which you can watch below:

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