AI-powered soft skills assessment platform that uses neuroscience-based games to evaluate cognitive and emotional traits for better hiring decisions.
Pymetrics revolutionizes talent assessment by using neuroscience-based games and AI algorithms to evaluate candidates' soft skills, cognitive abilities, and personality traits. The platform replaces traditional personality questionnaires with engaging 12-minute game-based assessments that measure traits like attention, risk tolerance, fairness, and processing speed. Pymetrics' AI technology has been trained to identify patterns that correlate with job success while reducing bias based on demographics or background. The games are designed to be inherently fair across different populations, making hiring decisions more equitable and inclusive. For employers, Pymetrics provides detailed insights into how candidates' traits align with successful employees in similar roles, enabling more accurate hiring predictions. The platform helps organizations identify high-potential candidates who might be overlooked by traditional screening methods while ensuring diverse talent pipeline development. Pymetrics' approach is particularly effective for entry-level and early-career hiring where candidates may lack extensive work history but possess the cognitive and emotional traits for success. The platform provides both candidate assessment and ongoing employee development insights, helping organizations understand team dynamics and optimize talent deployment.
Twelve scientifically-designed games that measure cognitive and emotional traits through engaging tasks rather than traditional questionnaires.
Use Case:
Sales role candidates play attention and risk assessment games that predict their ability to handle rejection and identify opportunities.
Machine learning models trained to focus on job-relevant traits while actively reducing bias based on demographics, education, or background.
Use Case:
Algorithm identifies strong customer service candidates from diverse backgrounds by focusing on empathy and problem-solving rather than traditional credentials.
AI matches candidate traits with successful employee profiles for specific roles, providing predictive insights about job performance.
Use Case:
Engineering candidates are matched based on logical reasoning and attention to detail patterns that correlate with successful software developers.
Platform provides insights into how hiring practices affect diversity and inclusion, helping organizations build more equitable talent pipelines.
Use Case:
Company discovers their traditional hiring process favors certain demographics and adjusts criteria to focus on job-relevant traits.
Pricing information is available on the official website.
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