Semantic ad technology provider Peer39 is announcing the closing of its Series C round to the tune of $10.5M, pushing the total amount of funding raised to over $22M. The round was led by Israeli VC Evergreen Venture Partners and was joined by the company’s existing investors Canaan Partners, Dawntreader Ventures, Silicon Valley Bank, and JP Morgan.

Since taking an in-depth look at Peer39 nearly a year ago, the company has shifted its focus from developing its own ad network to leveraging its semantic ad platform to transform publishers’ remnant ad inventory into a premium one. The company claims that 70-80% of publisher impressions are sold today as remnant inventory, and that its technology is perfectly suited to analyze these pages so they can instead be used to serve top-tier advertising inventory.

Take news sites as an example: These will often categorize themselves as “News” in ad server profiles but in reality they publish content that varies in categories—finance, health, travel, etc. Peer39’s SemanticMatch technology analyzes these pages in real time to determine what they’re really about. Amiad Solomon (CEO) tells me that they are able to shift up to 70% of news content into more sellable categories. Peer39 also offers SemanticProtect, a collection of ‘brand-protecting’ algorithms that can identify whether pages possess content that can be classified as objectionable or sensitive to advertisers (i.e. crime, terror, politics).

Integrating with Peer39 requires publishers to add a small piece of JavaScript on their site. On page-load, a request is made to Peer39’s servers, which analyzes the data semantically and assigns the most relevant and profitable advertising channel for the given page. This is where much of the company’s semantic and data mining algorithms come into play. Results are sent back instantly to the publisher and integrated within its ad serving systems allowing the most profitable semantic ad (display or text) to be displayed.

This post was originally posted on TechCrunch.com where I cover the Israeli startup scene.

No venture capitalist’s week is complete without seeing a company in the semantic space holding steadfast to the assertion that its pre-money Round A valuation is a steal at $50 million. The situation wouldn’t be totally absurd if it were not for the facts that these technologies are mostly half-baked, or far from becoming a deployable product. And they are most definitely leaps and bounds from being able to generate revenue—let alone actually generating revenue at the time of their pre-money $50 million valuation pitch.

But in the middle of this circus is a modest and press-shy company called Peer39. The company, which has purposefully been under the publicity radar since its inception in 2006, is a promising example that semantic technologies have true monetization potential. Peer39 is demonstrating this thoroughly through semantic advertising, the next evolutionary step beyond behavioral advertising, which was preceded of course by contextual advertising.

Peer39 is spearheading this space with its semantic advertising network, which is on track to hit one billion impressions by the end of the year. Their network only handles display ads at the moment, charging advertisers based on a CPM (cost per thousand) or CPC (cost per click) basis.

In an interview with TechCrunch, Amiad Solomon, the company’s CEO, claims that through the networks’ 30 top-level categories and thousands of sub-categories, Peer39 is providing advertisers, on average, clickthrough-rate improvements of four times what they were getting before. Publishers hail from all verticals, including technology, automotive, finance, and health.

Powering Peer39’s ad network is SemanticMatch, an algorithmic engine able to perform precise matching of commercial offers with user-generated content content (blogs, forums, etc.). SemanticMatch employs natural language processing and machine learning to determine meanings, topics, categories and even sentiment. All this, mind you, is done in real-time and Peer39 does not employ cookies in any way, nipping many privacy-related concerns in the bud.

Peer39’s technology has been two and a half years in the making. The 44-strong Israeli R&D team includes the former VP of R&D at Nielsen Online, as well as scientists from the Technion Institute (Israel’s MIT) and the Israeli army’s prestigious intelligence units. Together they were able to tackle the challenges of breaking down text into small enough pieces to categorize text with algorithms that are 1) generic enough to be applicable across a wide variety of content categories, and 2) able to adapt themselves to new categories on-the-fly.

Unlike contextual analysis that seeks out key words, Peer39’s semantic analysis engine—SemanticMatch—looks at the entire page to derive its meaning and its relevant categories. Below are a couple of examples provided by the company (I’ve added the italics for emphasis):

Example 1: “Amazon is a great place to visit.”

Peer39’s Category Analysis: Travel, Brazil, South America.

Example 2: “Amazon is a great site to visit.”

Peer39’s Category Analysis: Ecommerce, Internet, Business and Finance.

Category granularity can go down to seven levels. For example:

Technology > Consumer Electronics > Digital Camera > Canon > Powershot > SD870 IS > SD870 IS Silver

Auto > Compact > GM > Chevrolet > Chevrolet Cobalt > Chevrolet Cobalt LS Sedan

Peer39 is also able to determine positive/negative sentiment. This is important because it allows Peer39 to offer its advertisers various brand protection thresholds, such as offensive content, negative content, mention of competitors, etc. Canon, for example, might not want to advertise on a page with a negative review of one of its cameras.

On the business execution level Peer39 is attempting to pull off a Tacoda or a Quigo exit. Both companies were able to develop sizeable ad networks by delivering quality ROI results and working closely with agencies.

The company has raised $11.7 million from Canaan Venture Partners, Dawntreader Ventures, and JP Morgan. (The company won’t disclose its pre-money valuation, but given how much it has raised, a valuation north of $50 million is a safe bet). Its board of advisers includes Eytan Elbaz, a co-founder of Applied Semantics (which was bought by Google and became the basis for AdSense) and the former president of Tacoda Daniel Jaye. Also, the company just announced that Matthew Goldestein, former SVP of Revenue Operations at Tacoda joined as COO.

This post was originally posted on TechCrunch.com where I cover the Israeli startup scene.