Apple snaps up 'dark data' intelligence startup Lattice Data

Lattice Data transforms so-called "dark data" into information usable by data analytics tools.

screen-shot-2017-05-15-at-06-59-18.jpg
Lattice Data

Apple has acquired Lattice Data, a data mining company which could give Apple a stronger talent pool in the artificial intelligence and analytics fields.

Over the weekend, TechCrunch reported that Lattice Data, born out of the statistical inference Stanford research project DeepDive in 2015, had been quietly purchased by Apple.

The company's mission is to "unlock the value in dark data for critical real-world problems," which involves unpacking unstructured text and images, otherwise known as "dark data," and transforming it into usable information by standard data analytics tools and software.

Apple later confirmed the acquisition to Fortune.

While financial details have not been disclosed, the deal is reportedly worth between $175 million and $200 million.

The Menlo Park, California-based firm was co-founded by lead DeepDive investigator Chris Re and Michael Cafarella, a computer science professor at the University of Michigan.

Under the terms of the acquisition, Apple will reportedly gain roughly 20 engineers that will join the iPad and iPhone maker's team, giving Apple a wider pool of data science and engineering specialists to tap for future projects.

Artificial intelligence and data analytics are gaining traction and as everything from mobile applications to virtual reality and cybersecurity now harness the technology, there is scope for tech vendors to create new, profitable revenue streams.

"Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans," Apple said in a statement.

Last year, Apple acquired Seattle-based artificial intelligence startup Turi in a deal worth roughly $200 million.

Newsletters

You have been successfully signed up. To sign up for more newsletters or to manage your account, visit the Newsletter Subscription Center.
See All
See All