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Reduced turnover rate by 22%

“Hiring Process Dramatically Improved”

Valentina Petrovich photo

Valentina Petrovich

Talent Acquisition Specialist

Hirenest application

Background, a small-scale tech enterprise specializing in AI and ML software solutions for various industries, employs a talented team of up to 50 specialists. However, the complex nature of the roles within the company presented a significant recruitment challenge. The company found itself spending extensive time on candidate vetting and interviews, often struggling to find highly qualified candidates. Additionally, Datatron faced high turnover rates, adding further strain to the recruitment process.

Objectives and Goals

To mitigate these issues, Datatron set specific goals for implementing, a leading recruitment and pre-employment assessment platform. Datatron aimed to streamline its recruitment process, primarily focusing on roles related to AI and ML software development. Their hopes were pinned on to decrease time-to-hire, enhance the quality of selected candidates, and eventually reduce turnover rates.


To accomplish these goals, was integrated into Datatron's recruitment workflow. The platform was deployed for initial assessments of candidates, focusing on evaluating their technical skills, a critical aspect in the AI and ML software development field.


The implementation of led to a profound improvement in Datatron's recruitment process. The platform's systematic and efficient assessment allowed Datatron to reduce the average time-to-hire from 45 days to just 30 days, marking a significant 33% improvement. This substantial decrease highlighted's potential in speeding up the hiring process without compromising on the thoroughness of candidate evaluation.

Furthermore, the quality of new hires improved considerably. The precision of's assessments meant that candidates with a higher match to the job requirements were identified and selected. This improvement was reflected in the significant decrease in the turnover rate — from an alarming 32% to a more acceptable 10% within the first year of employment. This drop confirmed that the new hires were well-suited to their roles and satisfied with their job conditions, leading to longer tenure.

In addition, the cost per hire also decreased. Less time spent on interviewing and onboarding, thanks to's efficient pre-employment assessments, led to notable cost savings. These savings further underscored the financial benefits of implementing the platform.

Future Plans

Due to the significant improvement in their recruitment process, Datatron plans to continue using for their AI and ML software development roles. The platform's efficiency and effectiveness have proven invaluable in enhancing the quality of hires and reducing the time-to-hire, leading to improved operational productivity.

Encouraged by the success, Datatron is also considering extending the use of to other technical roles within the company. The potential of in identifying the right candidates for complex roles offers a promising solution to the ongoing challenge of technical recruitment. Thus, it appears that will continue to play a critical role in Datatron's hiring strategy.

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