The Netherlands-based Pera, a talent assessment, HR tech, and predictive hiring software, announced on Wednesday, April 12, that it has secured €5M in a fresh round of funding.
The investment came from the Brabant Development Agency (BOM) and current shareholders, including ECG Ventures.
Pera: Everything you need to know
Founded in 2015 by Rina Joosten-Rabou, Summer Xia and Robin Young, Pera’s goal is to make the ‘time-consuming, biased, and inaccurate professional selection process’ smarter and faster.
Pera says its analysis is naturally diverse and inclusive unlike other tools as it focuses solely on objective aspects of applicants that are important for employment success.
Well-known corporations such as L’Oréal, UPL, and LyondellBasell, as well as impact firms like Heliox and HeadFirst, are now collaborating with this Dutch startup’s technology.
Joosten-Rabou says, “Companies are struggling with important issues. Look at the energy transition. You need the right people and skills for that. But who are they and how do you find them?”
“The change agents of the future look different. Pera has spent years researching what leads to success in jobs and the answer is often completely different to what people think.”
“We can determine success after hiring much more precisely than a CV, a game or a conversation from the answer and language used. So quality increases.”
“Because the method does not look at origin or background, we also discover candidates that would go unnoticed, and we tap into new talent groups. Therefore, ensuring more diversity based on talent and potential, not on background or experience,” adds Joosten-Rabou.
Currently, the Dutch company has over 5.5 million professionals in its database and seven years of scientific research into organisational performance.
What is Pera’s method based on?
Joosten-Rabou mentions in a statement that the research behind Pera’s approach is based on over 30 years of science where it has been proven that people’s communication contains subliminal clues about their motivations, personalities, and behaviour.
Pera’s team has concentrated on gathering substantial data sets in recent years to serve as the foundation for its algorithms.
Additionally, they have also overcome significant machine learning hurdles via research and development so that businesses may generate reliable predictions even at the team level inside their organisation.
Pera says its platform is by design inclusive, equal, and diverse. Instead of what individuals write, the company’s algorithm examines how they write.
It simply has no prejudice or opinion and automatically ignores factors like education, work history, and ethnic origin. It then makes talent available that was previously unrecognised.
Capital utilisation
Pera says it will use the funds to further help companies strengthen their competitive position by identifying the right talent. The money will also help the company further develop its platform, the Pera Skope, to expand its position in the Benelux and the UK.
In addition, the company wants to consistently add intelligence for users, for example for specific IT profiles.
“We want to be the basis for every HR decision: who to hire, who to develop and who to promote”, says CEO Rina Joosten-Rabou.
Difference between ChatGPT and Pera
According to CEO Rina Joosten-Rabou, “The only similarity is that both ChatGPT and Pera are based on language analysis.”
“ChatGPT is a huge, complex language model that produces language. It currently generates text based on pure statistical relevance. ChatGPT has not yet been taught to reason.”
Pera offers insights on professional skills and how they influence and contribute to success in a position or organisation. This is accomplished by examining each applicant’s or employee’s own responses to the three open-ended questions in a digital interview.
Joosten-Rabou says that the questions are carried out by the company’s research tool Pera Skope. It uses language analysis to compare the responses to a special dataset that describes the professional achievement of other people.
“These datasets have been collected in collaboration with companies and are not freely available. This means the data input, outcomes, validity and transparency of the models can be easily checked,” adds Joosten-Rabou.
Pera has already conducted an experiment to evaluate the impact of ChatGPT. Click here to find out.
01
Job board for modern workforce: How Remote Talent helps jobseekers find truly remote, distributed work