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Whiz's autonomous cleaning greatly reduces the burden on cleaning staff. Whiz can undertake large-scale vacuuming, wiping and other repetitive heavy work, reducing the time and intensity of manual operation. Cleaning staff simply place robots in areas that need cleaning and can then focus on other more complex and human-skilled tasks, such as housekeeping and toilet cleaning. As a result, cleaning staff can allocate their time and energy more efficiently, increasing their overall productivity.


Cleaning staff can manually enter the cleaning route and requirements into the machine, and then reuse the cleaning solution. Whiz also sends notifications when tasks are completed, the battery is running low, and the dust bag is full, alerting the cleaning staff to adjust and intervene. As a result, Whiz's automatic cleaning is by no means a complete exclusion of the manual, but an organic collaboration with the cleaning staff.


Such human-machine collaboration is not only reflected in the improvement of work efficiency, but also can improve the work experience and satisfaction of employees. By delegating heavy and repetitive cleaning tasks to robots, cleaning employees are able to free themselves from drudgery and focus on more challenging tasks. This shift can increase employee motivation and enhance their sense of belonging to their work. At the same time, human-machine collaboration also provides learning and development opportunities for employees, who can learn new skills and knowledge by working with robots to enhance their competitiveness.


Whiz are not designed to replace human cleaners, but to collaborate efficiently with cleaning staff to optimize human resource allocation.

 


Value

Enhance Cleaning Efficiency

Repeat established routes 

 achieve efficient automatic cleaning


Free Up Human Resources

Take on heavy and repetitive tasks

allowing staff to focus on higher-level cleaning


Flexible Support and Complementarity

Complement manual and automatic efforts

make timely adjustments and improvements


Use Case

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