The Robotic Process Automation (RPA) market has been growing steadily in recent years, and this growth is expected to continue. Due to the demand for software of this nature, various responses have emerged, from startups that have become giants, such as UiPath, to major players that are expanding their offerings in this segment, like Microsoft and SAP. It is clear that there is a demand for “low code” solutions that allow the abstraction of creating repetitive process automation flows, as well as the ability to orchestrate and govern the respective automation initiatives.
Creating software that enables the instantiation of process automation flows requires a significant investment in software engineering. It is complex to build a platform that encompasses all the aspects that RPA entails, to the extent that its value is appreciated based on the automation scenarios and integrations it enables. Thus, the need to maintain such a platform in full operation and simultaneously work on its innovation requires multiple teams with diverse skills and responsibilities. Consider UiPath, a leading tool in this segment, with almost 4500 registered employees on LinkedIn. Hence, the existence of licensing associated with these platforms is entirely justified.
The various RPA software offerings in the market also exhibit different morphologies. Some are complete enterprise platforms, while others focus more on “low code” approaches or expand the capability of native programming languages. Some software concentrates on specific types of automations, integrations, and platforms. The same applies to implementing companies like Engibots, which focus on specific domains, software, and industries, enabling them to provide a comprehensive solution to the end customer to solve the specific issues of their organization.
Thus, we outline the main forms of RPA software licensing:
Community or Limited Versions
These versions may present various limitations in terms of functionality or resource usage. They are essentially intended for learning, creating processes in development environments, crafting proof of concepts, or limited-scope automations. They are an excellent means to gain insight into functionalities and explore validation scenarios.
Per Robot
Robot-based licensing is a common type in the industry, where a corresponding license is acquired per execution node. The cost remains the same, regardless of whether a robot’s capacity is low or high. This type of licensing is aimed at organizations looking to strategically invest in process automation, as the goal is to maximize a robot’s hours to make the most of its allocation.
By Capacity
This model has been growing in recent years, particularly due to cloud resources, and is based on the principle of pay-per-use. As there is consumption and activity by the robot or robots, this value is charged by the minute or hour at the end of the month to the end customer. Capacity-based licensing can be an excellent alternative for clients aiming for a gradual adoption of automation, with fewer risks. The focus of this licensing strategy is to maximize execution efficiency, aiming to lower licensing costs.
By Functionality
Several platforms have adopted the functionality-based licensing model for complementary or advanced platform services, such as specific connectors or document reading. These functionalities aim to amplify a robot’s basic capabilities to enable it to perform more complex and comprehensive tasks, allowing even more robotic work to be liberated from human employees.
Of course, this is a fairly generalized description of licensing models, as each platform has its own peculiarities and variations based on the typology of robots and automations to be developed.
However, it is important to consider that each organization will have its specific needs and ambitions regarding automation, which is why it is recommended to scrutinize and evaluate the appropriate tool, as well as the respective licensing model. This is precisely the knowledge and support that the Engibots team provides to its clients, ensuring the structured success of their automation programs and the adoption of RPA tools.
