Bias-free hiring

Built for talent teams, loved by candidates

ATTRACT MORE
MUCH FASTER
IMPROVE RETENTION
REMOVE BIAS
DRIVE EFFICIENCY
HIRE BETTER
ATTRACT MORE
MUCH FASTER
IMPROVE RETENTION
REMOVE BIAS
DRIVE EFFICIENCY
HIRE BETTER

Unlock greater retention and a bias-free hiring process. We assess over 70 data points to identify the right-fit candidates, not just by CVs - driving diversity, lower recruitment costs and improved retention.

Delivering Hiring Outcomes

People matched by urfuture stay longer because their motivations & hygiene factors align with the job and career.

urfuture Career Match

100%

CV & Education

50%

2.0X

Less Terminations

Due to increased retention organisations drive down their recruitment costs with less turnover hiring.

urfuture Career Match

100%

CV & Education

80%

1.3X

Reduction in Costs

When basing hiring decision on scientifically proven predictors unconscious bias is reduced.

urfuture Career Match

100%

CV & Education

33%

3.0X

Increased Diversity

People selected on their soft skills over hard skills with urfuture produce more results faster..

urfuture Career Match

100%

CV & Education

60%

1.7X

Improved Performance

how we built it

Behavioural Science.

urfuture’s predictive technology is based entirely on Behavioural Science. By analysing over 90+ behavioural data points for each individual, we understand exactly what motivates their behaviours on a daily basis.

AI + Machine Learning.

urfuture has engineered a unique AI using ML that can process data from several thousand profiles to automatically generate predictive models, updating and fine tuning each one as candidates are successful.

Adaptive Technology.

By combining the power of the IRT model (Item Response Theory) with our proprietary scoring algorithms, we can reduce by half the screening time required to build an accurate and reliable assessment of a person’s unique talents and potential career & job matches.

Start smart matching now

40K
matches completed
4.3x
better prediction vs other Job Boards using CV’s
Impact by the numbers

Outperforming the industry

Time to put the CV in the past
CV Predictability
18%
78%
how IT WORKS

Built to see the person behind the paper

The secret to the unprecedented predictive power of urfuture lies in the way we collect and process hundreds of data points for each individual. Discover how our data collection modules are engineered to understand who people truly are, beyond their academic and social background.

Data capture.

Each candidate, upon signing up, undergoes a career matching assessment that evaluates their personality, basic needs, job motivators, and job satisfaction. This process generates 70 distinct data points per candidate, which are then stored and organised within our database, forming the foundational layer of candidate information.

Matching analysis.

Utilising behavioural science & ML, our algorithm matches candidates against 18 career paths, specific job postings, and 40 work-related traits. Each element is scored on a scale of 10. The results are displayed in user-friendly profiles for both candidates & companies, complete with instructional prompts and insights for better understanding.

Predictive Capabilities.

Our machine learning component analyses successful placements to identify common traits and patterns, driving a dynamic, predictive model. This delivers a refined system that enhances the accuracy of career matches based on real-world entry level employment outcomes.

Spotify predicts ur playlist we predict ur talent.

Behavioural Science & Machine Learning powers most sectors & now careers. Empower ur candidate decision making with Machine Learning & Logistic Regression The driving force behind smarter matching decisions and success in the modern world.

Netflix

Uses these techniques to predict user preferences and recommend movies and shows. It also predicts whether a user will like or click on a specific piece of content.

Experian

Logistic regression is used in credit scoring models to predict the likelihood of a borrower defaulting on a loan.

Spotify

Spotify uses machine learning, logistic regression, and AI to personalise music recommendations, predict preferences, and create custom playlists.

Booking.com

Uses these techniques to predict booking behaviours, recommend destinations, and optimise pricing strategies.

Remove hiring bias increase retention