AutoRecruiter is an AI-powered interviewing system developed by Goodspace. It aims to revolutionize the recruitment process by automating the initial interview stage.
By doing so, AutoRecruiter reduces time and costs while ensuring a more accurate and unbiased assessment of candidates. Employers can post job openings for free and receive candidate responses without any upfront cost.
They only pay when they find a suitable candidate and want to unlock their contact details. AutoRecruiter conducts in-depth video interviews and evaluates candidates, presenting top contenders with detailed reports.
It seamlessly integrates with popular talent discovery platforms like Naukri, Monster, and LinkedIn, reducing turnaround time to just 36 hours. The tool eliminates the need for front-line interviewers, substantially reducing recruitment costs.
Embracing AutoRecruiter allows organizations to transform their hiring process and gain a competitive edge in finding the best talent.
More details about AutoRecruiter
How does AutoRecruiter perform in-depth interviews?
AutoRecruiter performs in-depth interviews by asking relevant questions tailored to each job description. Its algorithm can delve into aspects beyond the capabilities of most recruiters, ensuring a detailed analysis of each candidate’s suitability for the role.
How does AutoRecruiter reduce hiring bias?
AutoRecruiter reduces hiring bias by using an AI-based algorithm for evaluation, which provides an unbiased assessment of candidates. It doesn’t rely on human instincts or subjective judgements, instead it uses defined parameters and data points to evaluate a candidate.
What specific features does AutoRecruiter have for tailored interviews?
AutoRecruiter features customized interviews that tailor to each job description. It asks relevant questions and evaluates candidates based on the specific qualifications and skills required for the job.
How is the goodness score from AutoRecruiter calculated?
The goodness score that AutoRecruiter assigns is calculated using Goodspace’s proprietary algorithm which considers feedback from the community and other data points to comprehensively assess the candidate’s strengths.
