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Cognitive Automation
for Staff Payroll

Reduces running costs and errors simultaneously.

Description of Problem

As an outsourced HR Services Provider, our User needs to process lots of information from various companies in its HR Payroll system. The User is responsible for updating their clients’ employees’ attendance and then generate payroll out of it.

However, the data transfer from the staff portal to the payroll system is a tedious task for the User as the number of clients keeps growing over years. Often, due to a high number of employees to process, errors tend to occur. Hence, manual double-checking is needed to ensure the payroll outcome is correct.


Client Overview:

The client is a HR services provider for SMEs in Asia for managing payroll needs.


Professional Services 

Processes Type:

Staff Payroll

How Gleematic Helps

Gleematic uses the ability of AI Machine Learning to extract, transform, classify data based on the User’s needs. Our software is able to access and work seamlessly with the User’s existing software/system to manage payroll needs. 

Data Extraction

Gleematic was able to extract information of each employee and place those information into the HR payroll system. Staff portals and HR payroll systems are not connected to each other. However, Gleematic was able to access the systems and transfer the data over.

Data Classification

Gleematic was able to recognize different conditions of leave, such as sick leave, maternity leave, etc., and categorize them into the different amounts of payment. There were huge volumes of data, but Gleematic was able to handle it quickly and accurately.

Data Entry

Gleematic was able to control the computer without human supervision, from running the applications to filling the data fields. It also updated existing information into the system to ensure data points are up-to-date with the current information.



Degree of Robotization: 75% Effort Automated


ROI: 3 Months

Human Error Rate Reduced


Manual Effort Reduction to 75%


Faster Processing Time: Reduction of 65%


More Standardization


High-Quality Improvement


No More Repetitive Administration


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