Time Detect

The Time Detect API uses machine learning to find irregularities in time and absence registrations, increasing approvers’ accuracy and efficiency.

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Peter can confidently focus on other tasksPeter can confidently focus on other tasks
An employee scans their ID while leaving work
Peter approves time and absence registrations for 500 employees
Their work hours are calculated
He logs into the time management software
Those hours are transferred to the HRM system
Registrations show irregularity scores and explanations
The employee can see their payroll data in real time
He reviews the irregular ones and auto approves the rest
The company frees up HR resources for employee development
Peter can confidently focus on other tasks

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Time and absence

Streamline the approval process for time and absence registrations with machine learning.

Time and absence

Streamline the approval process for time and absence registrations with machine learning.

How the API works

The Time Detect machine learning models are trained on historical time and absence data to learn the working patterns of the organisation, department, project, and specific employees. When new registrations are created or changed, the models assess how irregular they are, what fields contributed the most to the irregularity score, and how much they contributed to the total score. When registrations are approved, they’re sent to the models to make sure that they’re continuously learning and keeping up with the working patterns.

In addition to making the approvers more accurate and efficient by providing irregularity scores and explanations for all registrations, the API can also be used by the employees themselves in real time. This is the most efficient way of correcting errors in time registrations.

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