There’s absolutely nothing efficient about sorting through 30,000 resumes by hand. Recruiters spend months evaluating applicants only to have great prospective candidates get lost in the pile. On the stage of TechCrunch’s Startup Battlefield, French startup Riminder made the case for how its deep learning-powered platform could augment recruiters — helping them better surface ideal contenders for job openings.
Riminder generates candidate rankings for open jobs by comparing applicant resumes against resumes from current employees and others in the world with similar job titles. Behind the curtain, Riminder uses a cocktail of computer vision and natural language processing to build profiles of what ideal resumes should look like for specific roles.
The goal is to make sure recruiters have the information they need to judge candidates on both their ability to fit into company culture and their mastery of key skills.
When demonstrating Riminder’s value to a potential recruiting client, the team often runs tests on historical data. This data makes it easy to compare the platform’s automated short list with a human generated list.
“When we compared results, recruiters found 3x more candidates they were interested in, they just weren’t using the right keywords,” explained Mouhidine Seiv, founder of Riminder.
Aside from helping recruiters sort through applications, the tool also has the potential to make hiring more fair. Seiv told me that some companies refuse to accept applications from international candidates simply because they don’t feel comfortable evaluating the applications. Because Riminder has seen resumes from around the world, regional variations are easy to accommodate.
Another perk of Riminder is that it can automatically reroute applications to other open positions if it notices a better fit. This increases the likelihood that the right applicant will be considered for the right job.
The objective of Riminder isn’t to replace recruiters. Humans still provide regular feedback on automated rankings and are ultimately better suited to be the final gatekeepers, interviewing and issuing acceptance and rejection letters to applicants.
The company participated in the CentraleSupelec Incubator and is currently running betas with companies like Uber and Blablacar. It’s currently marketing an enterprise-based offering charged on a per-user, per-year basis, a teams contact charged on a per-job title, per-month basis and a per-resume API offering.