Trapit Adapts AI-Driven Personal Search for Paying Customers
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use Trapit to cut through the noise, delivering content recommendations tailored to viewers’ personal interests.
Griffiths and Notthaft say there are more such deals in the works as Trapit matures from a fancy consumer search engine into a white-label discovery platform, available to any company that wants to make it easier for people to navigate large collections of content.
“We have terrific technology under the hood, and our theory was that there were customers who would pay for that differentiation, but they were probably not consumers,” Griffiths told me in October. “I think what you will see over the next few months is not so much us pursuing the consumer under the Trapit brand but other brands who already have an audience using Trapit to provide a better experience for their customers.”
In fact, you can think of Trapit’s Web and mobile apps as prototypes for the tools the startup plans to sell to third parties. Imagine, for example, a rebranded version of Trapit’s iPad app with pre-specified traps that guide users to content owned or curated by a particular company. Such an app might be useful as a marketing tool, a way to repurpose archival content, or a research aid for employees.
A white-label Trapit app for State Farm employees, for instance, might include traps highlighting news about insurance regulation or natural disasters. A Condé Nast app might include traps full of articles from Vanity Fair or Wired. (Those are just examples I made up—Trapit isn’t ready to say which companies it’s actually working with, beyond Astro.)
“This isn’t just a consumer app. The plan all along has been to expose this to business,” says Griffiths. But testing the app first on the broad consumer market was good practice, he says, because it forced the company to beef up its classification algorithms to handle almost any subject. Now the company can start narrowing down its filters so they understand the lexicons of specific markets. “The view was that if we started out very narrow, it would be much more difficult to broaden out later, and we were smart enough to realize there would be all softs of use cases that would emerge that we had never thought of,” Griffiths says. “That said, we never guessed that our first major partner would be a media conglomerate in southeast Asia that would want to use Trapit as a recommendation engine for movies and TV.”
But while the company is putting much of its effort into helping other companies solve their content management problems, it will also continue to refine the free consumer apps, which fill a niche that other browsing tools don’t. “We are often compared to things like Pulse and Flipboard, but we consider those to be the next generation of social RSS readers,” says Nothhaft. “We see Trapit as something quite different from that—it’s really a new way to browse the Web.”
Most of today’s social news readers only show users articles from publications they’ve subscribed to via an RSS aggregator like Google Reader, or links that their friends have shared on Facebook or Twitter. Trapit is broader, pulling in hundreds of articles for each trap from tens of thousands of sites, each of which has been vetted by a human to make sure it’s not a scraping site or content farm. That makes Trapit “unique in terms of its ability to handle a broad range of topics but also bring back high-quality content,” Nothhaft argues.
For real news junkies, the company sees an opportunity to build a subscription-based “prosumer” version of the Trapit tablet app with “more horsepower,” Nothhaft says. “There are features that might be appreciated by only three to five percent of our users, but they might be willing to pay something analogous to what Evernote is charging,” he says. (The premium version of Evernote’s online notekeeping service costs $45 per year.) But there will always be a free, basic version of Trapit, Nothhaft says—if only because “it’s the best form of marketing for the technology that we have.”
As with Siri, consumers may not know or care about the heavy-duty, DoD-funded personalization algorithms under Trapit’s hood. But if the software can find users what they want faster and more reliably, Griffiths and Nothhaft reason, there ought to be parties out there who are willing to underwrite the experience. I’ll check back with them later and let you know how that bet panned out.