Analyze and predict employee turnover, now with the full power of AI

Prevent talent drain with Nailted AI's predictive analytics. Identify who's at risk and take action before it's too late.

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Find out who is about to leave

The key to pinpointing where to focus your efforts

Identify groups at risk

Each group within the company faces unique situations. Analyze and understand the risk of disengagement in different departments, specific locations or any group with common attributes.

Individual-level exit probability insights

Analyze which team members have a high probability of leaving the company. By identifying these employees, you will be able to launch tailored retention initiatives.

Understand why they leave

Uncover data connections to employee engagement

Gain complete insights into your employee turnover

Our smart dashboard lets you monitor churn and its causes, analyze trends, and evaluate the effectiveness of your retention initiatives over time.

Add context with engagement data

Turnover isn’t isolated. Combining employee turnover and engagement data helps you pinpoint focus areas, address causes, and enhance talent retention.

Share and present your analysis effectively

Present information visually, intuitively, and accessibly for all employees, both inside and outside the People and HR teams, enabling informed, data-driven decisions collaboratively.

The investment even your finance department will applaud

Keeping your team is the best investment you can make

Maximize your ROI by preventing every departure

Every employee who remains with your company can save up to $20,000. Plus, those with more than three years of experience are 67% more likely to surpass their performance objectives.

Higher retention means greater savings

Each percentage point in retention improvement can generate 1-2% savings in labor costs and a 1% increase in productivity.

The investment even your finance department will applaud

*Turnover costs range from 30% to 150% of gross salary depending on seniority, role and degree of specialisation. We use 65% as an average to simplify this calculation.

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