/// Captricity Inches Toward the Holy Grail of Handwriting Recognition, One Data Field at a Time
I take handwritten notes about many of the people I interview and events I attend. It’s not the most efficient process, but a small notepad is unobtrusive and never runs out of batteries. Eventually, my notepads fill up (like my current one just did; yesterday, I wrote on the backs of pages because I didn’t have a spare ready), and they go to live on a shelf in an entirely unhelpful pile of lookalikes. So one technological breakthrough I’m personally interested in seeing come to fruition is an excellent handwriting-recognition scanner. And, so far, despite some placeholder efforts from folks like Evernote and Moleskine , I haven’t seen it. A 12-person Berkeley-based startup called Captricity seems to be on its way there. Currently, it analyzes handwritten data that’s entered in structured forms, for the benefit of governments, nonprofits, health-care organizations and researchers. Later this year, Captricity plans to offer a more free-form product, founder and CEO Kuang Chen told me yesterday. Chen, who raised raised $4.5 million from investors including the Social+Capital Partnership, the Knight Foundation, Atlas Venture and Mitch Kapor, after making a startup out of his Ph.D. research in Tanzania and Uganda, said he has a higher mission of “liberating data for any organization.” “If I meet someone I don’t want to talk to, and they ask me what I do, I say, ‘data entry,’” Chen said. “It isn’t sexy, but this is a very real problem.” Captricity founder and CEO Kuang Chen How Captricity currently works is this: Users upload empty forms, then virtually draw data fields onto the form, then scan lots of filled-out paper forms using the Captricity iPhone app or a scanner, wait about 30 minutes for the first 30 documents, and then receive a spreadsheet of answers, and review flagged concerns.