Harver raises $8.1M to replace the tedious trawl through résumés with an AI


The problem of dealing with CVs during the hiring process is a perennial one. There are a number of approaches and there are various assessment companies and recruitment companies providing human services to do so. But it’s tough to get around the fact that having to read a lot of CVs is often just pure grunt work.

Imagine instead if you could apply machine-learning and a platform which self-trained and optimized, as opposed to using human recruiters.

This is in fact the approach of Harver. It’s now raised $8.1 million in a Series A funding led by Insight Venture Partners to scale the adoption of its AI-powered pre-selection platform, TalentPitch.

This is a platform designed to replace the resume by integrating with a company’s existing HR processes and systems, and applying predictive analytics to improve the recruitment process.

This latest raise takes its total funding to $11.4 million and it now includes Booking.com, Netflix, Zappos, OpenTable, Casper, Adecco and others as customers. It has clients across 13 countries and pre-selects job candidates in 42 languages and has also today formally launched in the US.

How Harver works is that it replaces the resume.

Candidates apply for the job using a variety of modules, including: knockout questions that help work out if this is the right person from the start, then a company/culture video tour, real-life judgment tests, personality testing, intelligence testing, language testing, games that assess candidate skills and more. During the process, Harver’s algorithms gather relevant data and calculate a candidate’s propensity for success in the job role, they say.

Harver CEO and founder, Barend Raaff says: “Resumes have become nearly obsolete at predicting the value and success of a potential candidate in most of today’s jobs. Harver offers a fully automated recruitment solution grounded in big data that is completely agnostic to the job applicant.”

Sounds like the recruitment industry had better look out…

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