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Startup, Leap, is using AI to ensure tech job seekers get that interview

(BUSINESS NEWS) Two ex-googlers have created Leap and are using AI to make sure that techies are getting interviews.

bureau workey leap hiring culture, bias, job interview, job offer, elevator pitch

Hiring is a hard job

You are looking for that ideal job. Conversely, you may be looking for the ideal candidate for an important vacancy.

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LinkedIn, now under Microsoft, has become the default go-to resource. That status will soon face challenges from ambitious competitors.

Take a leap

Leap.ai, founded by two former Google executives, are making a bold claim: the LinkedIn model, a ubiquitous presence, can still be cumbersome. Looking to upend the antiquated “text crawler” methods that many HR departments use, they are promising a better way to match up candidates and employers— groundbreaking AI powered bots that will weigh candidate’s qualitative markers as efficiently as quantitative ones.

The result—an automated ideal match based on comprehensive aptitude and attitude variables, hitherto unheard of.

CEO Richard Liu was quoted saying, “We learned that hiring is hard. Your ability to learn, collaborate or take initiative are strong characteristics, but it is hard to get a feel for them from an interview”.

Users can sign up on the website or iOS app.

An algorithm matches candidate’s hiring criteria with available jobs, based on candidate profiles, which includes sections on self-assessment, personal values, and job preferences. “We not only send the user’s resume, but also an endorsement that explains why the candidate is a great fit for the company and role,” said Liu.

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If successful, such development promises to revolutionize job hunting, significantly cutting down on hiring timeline, resources expended and the need for HR intermediaries eliminated.

But for now, the startup is only focusing on tech jobs.

Artificial Intelligence, artificial success?

Will AI powered data fare any better? Especially, when the suggestion was compiled based on data gathered from job seekers and employers? As such, the matchup is not unlike what dating apps promise—a high degree of relatability.

Future profitability will provide a more direct answer.

In its current model, the new startup makes money only when it facilitates a hire. Although the company is yet to announce profits, at least 70 per cent of their “matches” have passed the first rounds of interview.

Is that rate much higher than what LinkedIn achieves? That data seems to be missing, perhaps because the specific metrics are not being tracked.

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Candidate matches are focused on five cities at present—Austin, Silicon Valley, Boulder and New York. However, since there is a lot of demand amongst Asian companies to re-acquire talents back from the America, Leap.ai has plans to expand globally. Interestingly, ZhenFund of China, a major Asian tech VC, has been the leading investor in the company.

“We’re actively seeking opportunities in China [but] we want to make sure we are well established in the U.S. before moving into China,” Liu said. “We’ve set our targets for the U.S., China and India from day one.”

The underdog

Founded under two years ago, the company has only 10 staff (half of whom were hired via their service). Their small size, however, is not stopping the startup from dreaming big. They want to build a mentorship opportunity— guiding young employees through career goals with helpful AI powered data.

Exactly how that goal would be realized remains unclear at this stage.

For now, despite boasting 50 customers including Dropbox, Uber or Chinese companies like Baidu and Didi, the company would require more seed money to become competitive.

It is perhaps ironic that the best place to get a quick background on the founders of the startup that is daring to challenge Linkedin, is in fact, Linkedin.

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#Leap

Barnil is a Staff Writer at The American Genius. With a Master's Degree in International Relations, Barnil is a Research Assistant at UT, Austin. When he hikes, he falls. When he swims, he sinks. When he drives, others honk. But when he writes, people read.

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