Cygnific handles thousands of customer service tickets every day. With colleagues and opening hours all over the world, managing shifts and time off can be a challenge. A new HR system ensured that colleagues could submit requests themselves. However, daily manual transformations on the data were required to be able to process it in the accounting tool.

Challenge 
How can we connect the HR solution with the accounting for all schedules and leave requests without human mutations.

Solution

Apply for leave and schedule working hours yourself

For Cygnific, Hemisphere developed a data pipeline in Azure Data Factory to connect the two applications in real time. With this link, the more than a thousand employees are now able to submit their leave and roster easily and quickly and it is well in the books. This automated a costly manual step (3FTE) and significantly reduced the chance of errors in the data.
Data

Data

Daily leave requests from 1500+ employees
Technology

Technology

MS Azure DataFactory
Scope

Scope

Development, Test and Implementation
Planning

Planning

Realized in 6 months

Level 4

AI optimization & implementation

AI is never a standalone solution. It requires a lot of fine-tuning and creating the right conditions to successfully land a Machine Learning model in an organization. Hemisphere knows what it takes to take these models to the next level. 

There are dozens of reasons why a model does not make it to implementation. Quality of (input) data, availability & costs of sufficient computing power and management are all well-known examples.

Hemisphere works with you to see what is needed to get more out of your AI solution. You can contact us from cleaning data and setting up HPC instances to offering customized Machine Learning SLAs.

Level 3

New AI model design

A costly hick-up in your process and do you have the feeling that only an AI solution can answer this? 

Hemisphere closely follows global AI development. This gives us a good idea of what is possible today. We have mastered various AI techniques on a broad level.

As a result, in most cases up to 80% of the final solution can be achieved in a design sprint of 2 weeks.

Level 2

Data engineering

The shift to cloud services offers organizations the opportunity to simplify their data processing. Companies that currently rely on batch processing can now implement continuous processing methods without disrupting their current processes. Rather than expensive rip-and-replace, the implementation can be incremental and evolutionary. 

By following the Extract-Transform-Load (ETL) methodology, data is processed and passed on in a qualitative and safe manner. This reduces the chance of errors in the data and provides the management team with the right data to base their decisions on.

Level 1

Data research

Data contains rich and often real-time information for a wealth of applications. By analyzing the large influx of customer contacts (anonymously), you are able to gain almost real-time insight into customer needs. Based on these insights, it is also possible to hyper personalize the offer. 

Hemisphere helps you make analyzes to understand the different trends and opportunities at the micro level. By responding to this, you exceed customer expectations and gain trust.