We are redrawing the boundaries of human potential assessment.

By combining our expertise in Behavioural Science with the most advanced Artificial Intelligence technologies (NLP, LLM, Machine Learning, and more), we are helping to revolutionise the assessment of potential and to advance knowledge linked to the prediction of human behaviour.

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AssessFirst algorithms are based on the ethical and responsible use of the most advanced Artificial Intelligence models.

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The challenges our Science teams tackle every day.

What we’re trying to achieve.


Understanding what influences human behaviour.

Our proprietary framework for understanding the psychological structure of individuals is based on models recognised by the international scientific community.

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Building robust solutions linked to the assessment of potential.

We create reliable and engaging solutions that enable ultra-precise quantification of an individual’s qualities.

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Creating relevant recommendation systems.

We design algorithms that enable recruiters and candidates to obtain targeted recommendations based on their specific profile.

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Maximising - and enriching - the quality of our predictions.

All our algorithms are constantly monitored and enhanced to ensure that our recommendations are as relevant as possible.

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We strive to understand what makes each human being unique.

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More than 750 data points taken into account.


Personality enables us to understand how a person tends to behave ‘naturally’ and also in stressful situations.

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Motivations enable us to identify the situations and environments that a person seeks out, as well as those that they tend to avoid.

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Cognitive abilities.

Cognitive abilities provide information about a person’s ability to learn quickly and solve problems of varying complexity.

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Our technologies handle phenomenal complexity... and deliver practical information in an easy-to-understand format.

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Here are just a few examples of the technologies we have developed.

Behavioural Assessments.

We create and validate all our assessment modules using the latest generation of ML (Machine Learning) models. In particular, we use NLP (Natural Language Processing) technology and image analysis.

This approach enables us to guarantee a level of precision unmatched to date.

Combined with item response theory (IRT) for scoring, this approach enables us to offer our users an in-depth understanding of their personality, motivations and reasoning abilities.

Tech Stack :

  • ML (Machine Learning)
  • NLP (Natural Language Processing)
  • IRT (Item Response Theory)

Automated Predictive Models.

The combination of LLM technologies (Large Language Models) and Sentence Transformers (DistilBERT model) enables us to extract fundamental elements from standard job descriptions – such as skills – and translate them into relevant personality and motivation dimensions.

These dimensions can then be used to create predictive models to anticipate performance and commitment in the targeted positions.

We then apply a ‘multi-penalty’ optimisation process to ensure that these models are fair, avoiding any discrimination against specific groups.

Tech Stack :

  • LLM (Large Language Models)
  • MiniLM (Sentence Transformer)
  • Optuna Framework (Multi-penalty optimisation)

Contact based Models.

We have developed a proprietary technology that identifies the personality and motivation dimensions that determine performance, based on an analysis of the profiles of current employees.

Our model identifies the most predictive dimensions using logistic regression.

Advanced model tuning is carried out using PyTorch. To guarantee the fairness of the model generated and avoid bias, our multi-penalty optimisation is refined with the Optuna framework, guaranteeing models that are unbiased towards any specific group.

Tech Stack :

  • Logistic regression (Statistical Analysis)
  • PyTorch (Model Fine Tuning)
  • Optuna Framework (Multi-penalty optimisation)

Job Similarity Algorithms.

Using the extensive ESCO occupational directory and the advanced MiniLM phrase transformer, our ‘Job Similarity’ algorithm identifies associated job roles in the semantic space.

This technology guarantees a precise match in our Sourcing and Career Path functionalities, optimising recruiters’ searches and guiding candidates effectively.

The result is an innovative and effective solution that completely redefines job recommendation and career guidance.

Tech Stack :

  • ESCO Framework (Jobs Directory)
  • MiniLM (Sentence Transformer)

The impact of AssessFirst Science.

For you, for your company and for your candidates.


More performance

People selected on the basis of their talents (with AssessFirst) produce more results, more quickly.

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Less staff turnover

The people we recruit stay longer because their motivations are better aligned with the job and the company culture.

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More diversity

Recruiting on the basis of potential frees you from discriminatory criteria (age, gender, schools attended, disabilities, etc.).

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Find out how our customers are improving their talent management.

Improved Candidate Experience.

Since we deployed AssessFirst, we have increased candidate satisfaction by 77%, while reducing staff turnover by 34%.

Candidate satisfaction 77%
Staff churn 34%
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Acceleration of the recruitment process.

AssessFirst saved us time in our recruitment process. This allowed us to reallocate this saved time and enhance the candidate experience and enhance our employer brand.

Acceleration of recruitment 67%
Improvement of employer brand 59%
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Making skills assessment more reliable.

The Competency Framework functionality offered by Assessfirst offers us a reliable skills assessment model that is easy to use and perfectly aligned with our company culture.

Model reliability 97%
Employee satisfaction 86%
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