No matter what language you speak, when you look at a Web page, you can get a good idea of the purpose of the different elements on it—whether they're images, videos, text, music, or ads. It's not so easy for machines to do the same, though.

That's where Diffbot hopes to make a difference. The startup, based in Palo Alto, California, offers application programming interfaces that make it possible for machines to "read" the various objects that make up Web pages. This could enable a publisher to repurpose the contents of pages for a mobile app, or help a startup build a price-comparison site.

The company's efforts come at a time when some tech titans are also working to add more structure to the vast amount of data on the Web. Google, for example, recently unveiled the Knowledge Graph, an effort to identify the meaning of search queries and return relevant results, rather than simply matching the text of a query with Web pages that include the same words. But these efforts usually rely on people to help by tagging Web content to infer meaning.

John Davi, Diffbot's vice president of product, says that at its heart, the company is about taking the visual learning technology that propels self-driving cars forward on a road and applying it to Web pages.