In a world where VC money for tech-enabled startup isn’t necessarily flowing like water, it’s nice to be singled out for a cash infusion. That was the case a couple of weeks ago for Swedish-based semantic text analytics API-development vendor Saplo, which scored $500,000 in seed funding from investors including IKEA Group parent company the Stichting INGKA Foundation chairman Goran Grosskopf and SOVA retail store chain founder Martin Liljeberg. Founded by Mattias Tyrberg, the SeedCamp Europe 2008 finalist this month followed its money win with an update to its Tags & Mach widget, which it’s built entirely on its API. The new widget, primarily used by news sites in its home country, to display entity tags and related articles based on what the user is currently reading, and now adds features such as the ability to edit those entity tags.

Home is where the API is for Saplo, which Tyrberg co-founded with psychology professor Sverker Sikström, who’d been working for ten years on the science of sentiment analysis. The seed funding will go for further development of its API, but the company actually began life with the idea of building its own social media analysis applications. Faced with the tumbling economy it determined it would do better to focus on building a platform to power others’ efforts. The API for accessing services including entity tagging, topic tags, related and similar articles, contextual recognition and sentiment analysis, is currently in a limited beta release.

Tyrberg admits there’s not a big market in Sweden to drink from its technology, so Saplo has ambitions to focus in on the U.S. “This year we have been developing our technology for the U.S. market, for English,” he says. “One of the key strengths of our technology is that we can adapt new languages very easily.” With a development staff of just 7 people, it took just one month to make its entity extraction capabilities work in English, he says. “That’s a very short time compared to, say, Open Calais, which has a lot more people and only supports a few languages,” he says.

What facilitates speed of execution? Tyrberg credits it to not using rules that are language-dependent when building the system, so it can find pieces of text with similar meanings, written in different languages. “Our rules are language-independent,” he says, so adaptation is mostly a matter of having someone who knows the new tongue to spend a few hours training data sets. Some competitors, he says, that use more language-dependent rules and also word lists can’t be as agile. “They have lists of people or organizations that they know this is a person or organization. We look more at articles and if a new person appears we don’t need to use any databases at all, so we can actually get from the text directly whether it’s a new person or new organization. That’s because it understands the context.”

The small start-up will face competitors with bigger presences. But Tyrberg is thinking of other ways to capitalize on the technology that will ring a bell with content providers if enabled as parts of their sites. He mentions this summer might see the development of a personal recommendation engine that utilizes the understanding of context to create filters for emails, RSS feeds and article content based on how users mark up what they read online. “So u have two contexts—one is I like or hate this, and when new text comes into the system you can compare to both contexts and say how similar is this article to the one I like or hate. If one is most likely to be like the text you like, then it gets presented, and those you don’t like aren’t shown or aren’t shown with the same amount of information,” he says.

Understanding those patterns and automating interests could have a role in internal enterprise Wikis or networks, as well. “You can use that for recommending each person in the organization to find what is most interesting for them,” which could be very different across titles from developers to CEOs. “It’s a huge market for the enterprise,” he says, adding that business intelligence technology also has a huge opportunity for getting closer to text analytics within five or so years. “I believe that right now BI companies are crunching lots of numbers, and visualizing them. What I think will change is you need to analyze the massive amounts of text both internal and external because that’s something that can be very important information for knowing how many products you will sell, and so on,” he says, noting the influence of things such as positive and negative sentiments expressed in media.

“I just want to be the platform to build all these kinds of services,” says the 26-year old Tyrberg, who by the way won Sweden’s 2009 Young Entrepreneur of the Year.

That makes me think it’s time we refreshed our look at the Semantic Web’s Young Guns – we’d love to hear from you the under-30-year-olds shaping the direction of the semantic web over the next decade that you think our audience should know about. So let us know who you’d like to see make the cut!

• Don’t forget to propose your startup for our Semantic Web Impact Awards. The deadline is Sept. 15.

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