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Soft skill assessments date back 50+ years - we've created a gamified assessment to determine someone’s potential fit or success in a role and mitigate bias.

pymetrics is converging modern cognitive science with cutting edge AI to accurately and scalably assess people to jobs 

Read about our unique approach

It Starts With Soft Skills

Cognitive science promotes equity + flexibility in the future of work

Advancements in cognitive science led to two primary differentiators for pymetrics soft skills:

  • Equity:  Unlike traditional tools, pymetrics' soft skills are evenly distributed across gender, race and socioeconomic status, making them the key to equitable soft skill assessment.
  • Flexibility:  pymetrics' soft skills platform is fit-based, understanding inherent fit to role rather than using a one-size-fits all approach or restrictive credentials.

Audited, fairness-optimized AI 

We can design AI to be both accurate and objective by using these three principles. First, we start with better data: evenly-distributed soft-skills data. Second, we only release algorithms if they meet stringent accuracy and unbiased standards (lacking disparate impact). Finally, we don’t ask you to take our word for it: we had our platform independently audited to ensure full transparency.

See full report here.

Read about our audit

Backed by research 

See all research

In the news 

The standards we follow 


Each step of the pymetrics process has been implemented in compliance with the Uniform Guidelines on Employee Selection Procedures (UGESP). This includes job analysis, criterion-related validation (concurrent validity and predictive validity), reliability, and fairness.


While the Equal Employment Opportunity Commission (EEOC) does not rubber-stamp assessment products as compliant or non-compliant with its guidelines, each step of the pymetrics process was designed with UGESP in mind and is implemented using methods that adhere to these regulations.

A broader community 

pymetrics is committed to contributing to scientific knowledge about ethical AI. We work with academics from a variety of disciplines including computer science, psychology, economics, and law, to provide new information about our technology that is transparent and useful for diverse audiences.