We continue the case study series of SoDA companies. The stories tell about how they managed to create, develop or implement products and services based on Microsoft Azure technology.
Grow Uperion
At Grow Uperion, we create solutions that support workers in achieving their company’s business objectives. The goals may be different, starting from sales targets and ending with training. The entire process is based on gamification mechanisms visualized in the form of objects developed individually, available on our platform. Our solution enables simple scaling of the number of users, which is an enormous advantage of the system in the context of achieving training objectives. The mechanics of the platform, based on visualization of effects, are a critical part of the system. Every participant has their own object to grow, indicating the achievement of an individual or group goals.
A certain level of integration with the client’s systems, that would make it possible for us to generate the appropriate reaction depending on the progress toward the objective defined together with the client, is necessary for implementing and visualizing progress in the form of growing objects. The goal may be an arbitrary sales target, warehouse inventory or performance of a task or sending of an e-mail with the appropriate content. Information flow between the platform and systems on the client’s side is essential.
This is where the first challenge appears — since there are several types of such systems, and integration associated with creating code for the purposes of implementation every time is ineffective from a business standpoint. Low-code or no-code solutions address these challenges, and the Azure Logic Apps package is a good example.
We decided to use this solution for several reasons:
- Easy integration with different systems
- Minimal engagement of programmers
- No servers
- Fees only for resources used
How do we use them in practice?
Azure Logic Apps allow us to connect to, e.g., the client’s ERP system and gain access to specific data. If an employee reports a sales result or performance of a specific task — simply put, when specific data flows into the system, Logic Apps detects them and triggers an action on the side of our system. Logic apps can also be scheduled to react if they do not receive data by a defined time. There are many possibilities.
The advantage of Azure Logic Apps is that data flows can be on multiple levels and trigger reactions in different Grow Uperion scenarios. Thanks to this, we are broadening the spectrum of potential external integrations of the client’s applications, and their result can be transposed not only to the growth of a single object but also trigger a wider reaction in a defined group. By means of this solution, users can observe their progress based on a diverse set of data and indicators, and they also see the combined reaction of the given group to which they belong. All of this is made possible by well-planned data flows.
One interesting function can be to apply the possibilities afforded by artificial intelligence, for example. Let’s take an example that is quite simple. Let us imagine a situation where we are training 1000 employees from 13 countries in Europe. One of the tasks is, for example, to send a photo showing a car. Normally, to complete this task, someone would have to physically evaluate 1000 messages. Thanks to Azure Logic Apps, an AI module trained to detect cars could be used to do this. The savings of time and resources are immense.
Azure Logic Apps make it possible to automate a series of processes, limit the use of valuable programmer resources and create diverse workflow scenarios between two independent systems. Thanks to this, our platform can gather data from external environments and perform specific tasks in a simple way, which makes our business scalable and creates many possibilities when it comes to adaptation to the client’s needs.
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