The definition of RPA
Robotic Process Automation (RPA) is a technology that uses software robots (“bots”) to automate repetitive, rule-based administrative tasks that are otherwise performed manually.
Robotic process automation makes it possible to quickly build and implement automated processes, reducing manual errors, lowering administrative costs and increasing productivity.
RPA is usually divided into two categories:
Attended Automation (Attended RPA)
Supervised automation involves a human and a software robot working together in real time. The technology is often used in front-office contexts where the employee initiates and monitors the process while the robot handles the repetitive tasks.
The monitored robot mimics the user's actions on the computer or in the browser, such as mouse clicks, data entry, or navigation between systems. This frees up time for higher business value tasks while increasing accuracy and reducing processing time.
Unattended automation (Unattended RPA)
Unattended automation occurs without human intervention. These robots operate autonomously in the background and can be initiated by scheduled events, triggers, or data flows. Unattended RPA is often used to manage large-scale processes across an organization, such as invoicing or data migration, where speed and reliability are critical.
By working around the clock and integrating with multiple systems in parallel, unattended robots help increase efficiency and reduce costs on a large scale.
How has RPA evolved?
RPA began as a way to automate simple, rule-based tasks like data entry and file management. The software robots imitated human actions in various systems and could quickly take over monotonous tasks. The result was more efficient processes, fewer errors and lower costs.
The technology grew out of older solutions like macros, screen scraping, and user interface testing . These early forms of automation laid the foundation for today's more advanced RPA, which has evolved as software architecture has become more open and processes have become more standardized.
As the technology matured, RPA moved from being point solutions to becoming a strategic part of companies’ digital transformation. Platforms began to support decision logic, API integrations, and central monitoring of robots, moving closer to broader process automation platforms.
The future of RPA
Today, the development has taken another step. Through low-code and no-code tools, business users can also create and customize automations themselves or with external help. Here, platforms like Softadmin® become a natural next step where automation no longer occurs in separate robots but as an integrated part of the entire system flow.
With support from Multisoft, organizations can build sustainable solutions that combine automation, integration, and business logic into a cohesive system.
The next step in development came when RPA began to be combined with intelligent technologies such as AI, machine learning, natural language processing, computer vision. This development, often called Intelligent Process Automation (IPA), Intelligent Automation (IA) or Hyperautomation , allows RPA to no longer just perform tasks, but also understand, interpret and learn from data.
Today, RPA is used to connect systems, manage complex flows, and free up human resources so your employees can do more value-added work. The technology has become a key component of modern process automation, but large-scale implementation still requires clear governance, change management , and long-term planning to be fully successful.
The difference between RPA and DPA
RPA is basically about automating a task, while DPA is more synonymous with a system that automates entire process flows, including integrations, interfaces and flexibility, and can be seen as a further development of Business Process Automation (BPA).
When you use RPA, you first define what needs to be automated, and then connect a bot that performs the task that a human performs in one or more systems.
RPA is therefore often change-sensitive. Changes to one or more systems or to your processes will potentially disrupt the automated process, and if you have multiple automations of this type set up, several of them will be disrupted.
A practical RPA example
Large IT consulting companies such as CGI, Atea and Knowit are working with RPA. For example, a customer in the public sector may be working with case management in the business. An administrator repeats repetitive manual logging in different systems.
RPA can then be applied to automate the process, and a “robot sequence” is built so that automation is a click away (supervised automation). When you see this problem on a larger scale, it means a huge amount of work time is saved.
A tailor-made automation solution
Multisoft also does this, the difference is that instead of using an RPA tool like UiPath, we use Softadmin which is tailored to your business needs and can scale with your business and processes (can be described as unattended automation via a system).
RPA can be seen as a more rules-based and limited way of automating. Consider how much more a Digital Process Automation system enhanced with AI could accomplish.
Multisoft has a customer satisfaction rate of 94% after completed implementation projects. For more than 30 years, we have worked based on the motto "We ♥ automation" and developed the low-code platform Softadmin.
With Softadmin, business and IT can work together to quickly go from idea to finished system, without long development cycles or extensive coding. This means that customized solutions can be delivered quickly and easily scaled up as needs grow or change.
