The Finnish Tax Administration selects Digital Workforce as its software robotics supplier

Digital Workforce has signed a service agreement with the Finnish Tax Administration to provide the organization with an extensive RPA-platform (Robotic Process Automation). The acquisition covers the licensing and delivery of software robots, solution training, support, maintenance and expert services. The RPA-platform is utilized across the entire Tax Administration.

The use of software robotics to automate the Tax Administration’s work processes has been investigated and tested since 2015. Through these investigations, the Tax Administration has identified RPA business benefits that include: reduction of costs and errors, more harmonized operations, inter-system integrations and increased process speed. All the identified benefits support the Tax administration’s strategic goals and translate into improvements in customer service.

As an Intelligent Process Automation (IPA) service provider, Digital Workforce has the flexibility to complement the capabilities of its software robots by extending its services – according to its customers’ needs – to cover other intelligent technologies.

Digital Workforce selected as the strategic partner to Finland’s largest healthcare district: HUS prepares to ramp up the use of software robots to boost efficiency and service quality

Digital Workforce has been selected as the strategic partner to Finland’s largest healthcare district following a competitive bidding. Digital Workforce will deliver software robots to Helsinki and Uusimaa healthcare district (HUS) as a cloud service, which can also be used to automate CE-marked clinical processes. The estimated total value of the acquisition is up to 1 300 000 euros.

Digital Workforce’s cloud-based digital workers enable the safe and agile automation of both administrative and clinical processes at HUS. Aside from software robotics, new technologies such as Machine Learning and Artificial Intelligence (AI) may be introduced to grow the digital workers’ capabilities in the future.

Digital Workforce is Finland’s leading processes automation service provider in both private and public healthcare. In addition to HUS, the company delivers digital workers to multiple other Finnish healthcare operators such as Espoo, Istekki, 2 M-IT, Eksote and PSHP.

More information

Tiina Leivo, Head of Healthcare
Digital Workforce
+358 50 1928

A guide into the world of intelligent process automation

The field of robotics is full of excitement and buzz-words, but it is often difficult to determine the concrete under the hype. The term Intelligent Process Automation, more commonly known as IPA, has recently joined the conversation. What is it all about? And why is it worth paying attention to?

What does IPA stand for?

IPA refers to a process automation solution, where the technology being used is smart – at least to some degree. There isn’t just one kind of IPA, rather the solution is tailored to fit the process requirements. The technologies utilised in the solution might include for example software robotics, chat bots, image recognition or machine learning. Put short, IPA is an umbrella term for a variety of different technologies that can be utilised (together) to automate processes.

IPA as a continuum of virtual work

It is reasonable to consider a company’s shift to using digital workforce as a continuation, where the journey starts at simple, repetitive and easily defined tasks. These routines of knowledge work are automated cost-efficiently with RPA (Robotic Process Automation), where every action of the robot is predefined in a manner following “if this then that”-logic. RPA best suits a situation, where different steps are repeated predictably and volumes are high – this way savings in expenses and the quality of operation rise enormously! RPA that is based on predetermined rules however doesn’t fit a situation, where steps can’t be well defined because there exists a large variety of possible actions following a situation.

In the next step of the continuum, focus shifts towards smart technologies, that take up tasks that require interpretation. To understand this step, it is useful to consider an RPA exception situation, where a software robot operating based on predetermined rules sends back a group of exceptions for the human worker to deal with. In practice, a situation like this might occur for example when a specific piece of information is logged in the used IT system’s open field in different formats. When the software robot processes the information, it only recognises the predetermined formats and reads the differing formats as errors. In a situation like this, a virtual worker utilising machine learning might provide a solution, by learning to identify that the different formats have the same meaning. If the smart virtual worker is delivered as a cloud-service, the solution also enables a flexible level of service, where more capacity and tools may be put to use when necessary.

Artificial intelligence in turn refers to completely autonomic systems, that can interact with their surroundings at any situation and reach their goals independently. These kinds of technologies are represented by for example IBM’s Watson and Google’s Alice. As computers’ abilities grow it becomes easier to recognise what technologies can’t be considered in terms of artificial intelligence, though defining true artificial intelligence remains difficult. For example, photo recognition – today considered to be routine technology – was previously considered a form of artificial intelligence.

Why is understanding the big picture so important?

The conversation around robotisation and future of work is often regrettably vague and leaves it unclear, what are the practical applications of the new technologies. Pumped up by the hype, it is easy to start doing things that sound great but do not meet needs in practice – at least not cost-efficiently or in a way that delivers on expectations. On the other hand, because the change in all fields only keeps accelerating, and because the competitive advantages reached by utilising virtual workers have been unprecedentedly large, this boat should not be missed!

The utilisation of virtual workforce should however always begin by considering the need, in a way that the choice of technology happens on the terms of the target. The best results are reached by climbing up from root to the top: transforming business processes into a digital form that can be utilised by robots and moving from rule-based automation towards smart solutions where the needs are clearly recognisable. The implementation of smart automation typically starts by recognising and prioritising the objectives. The concept of ‘IPA-continuum’ represents this way of thinking.

Intelligent Process Automation: A short glossary

Intelligent Process Automation, IPA

Intelligent Process Automation (IPA) refers to the practice of process automation with solutions that involve smart attributes. IPA solutions are tailored to the specific requirements of the target process by combining technologies like, chat bots, computer vision, machine learning and robotic process automation software.

Robotic Process Automation, RPA

Robotic Process Automation (RPA) refers to process automation with software robots. The robots are programmed to use the applications required for the execution of the target process in the same way as a human operator would. They always follow pre-programmed rules and are easy to integrate into existing business processes.

Software robot

Software robot is a software application that is used in robotic process automation to replace the actions of a human worker interacting with the user interface of a computer system. Software robots may have some vendor specific attributes, but implementing these technologies never requires changes to existing systems.

Enterprise RPA

Enterprise RPA refers to the use of RPA technology in a large and industrial manner to achieve automation requirements of a large enterprise. Enterprise RPA solutions are scalable, easily managed and maintained. These features are achieved by specialized services such as: managing component libraries that allow the re-use of automation objects, expert support, staff training, following and managing RPA performance, support in setting up internal robotic center of excellence.

Business Process Automation, BPA

Business Process Automation refers to a high-level strategy that aims to streamline all business processes. It involves recording – and re-designing- all processes within the business to digital format and then integrating them with an automation software.

Digital worker/ Virtual worker

Digital or virtual worker refers to a software robot that takes over a process or task otherwise performed by human workers. Digital workers deliver Robotic Process Automation (RPA) services where the used technology is a pre-programmable software.

Intelligent digital worker

An intelligent digital worker is a technology platform that combines pre-programmed software robots with different cognitive technologies. An intelligent digital worker is able to handle processes that consist of more complex tasks involving unstructured data and interpretation. Intelligent digital workers are used to deliver Intelligent Process Automation (IPA) services.

Robotic Center of Excellence, CoE

Robotic Center of Excellence (CoE) is the organization’s management center for the use of automation technologies. The job of the CoE-team is to create, measure and manage a virtual workforce that supports the organization’s strategic goals.

Robotic Desktop Automation, RDA

Robotic Desktop Automation (RDA) refers to computer-specific automation that is applied to speed-up or enhance the performance of a human worker using the desktop. While RPA technologies can be referred to as virtual workers, RDA technologies work hand-in-hand with their human counterpart and thus may be called virtual assistants.

Optical Character Recognition, OCR

Optical character recognition (OCR) refers to the conversion of images of typed or hand written text into machine encoded text. OCR programs analyze scanned-in images to detect light and dark areas in order to identify alphabetic letters and numeric digits. When a character is recognized, it is converted into code. OCR is often being used to digitize typed or handwritten information.

Natural Language Processing, NLP

Natural Language Processing (NLP) technologies enable computers to process large amounts of natural (human) language data. NLP technologies typically rely on machine learning to help them automatically learn new rules.

Computer Vision

Computer Vision technologies are used to enable computers to gain high-level understanding from digital images or videos. These technologies seek to automate tasks that would otherwise require the human visual system.


Chatbots are computer programs that can conduct a natural language conversation. They are designed to simulate a human conversation partner convincingly either via auditory or textual means. Depending on the level of sophistication of the solution, chatbots can make use of NLP technologies or analyze keywords.

Machine Learning, ML

Machine Learning (ML) gives computers the ability to “learn” (i.e. progressively improve performance on a specific task) by processing data. ML technologies can “learn” under supervision, i.e. learn general rules to map inputs to outputs based on a set of example inputs and their desired outputs. The “learning” may also be unsupervised, in which case no examples are given to the learning algorithm. Instead, it is left on its own to find structures from its inputs. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning).

Cognitive Computing, CC

Cognitive Computing (CC) describes technology platforms that involve cognitive technologies such as machine learning, natural language processing, computer vision, and chatbots. The purpose of cognitive computing is to combine these technologies to find meaning from and understand a data set at a higher level. Rather than just pure data or sensor streams, cognitive computing can deal with symbolic and conceptual information. Cognitive computing enables computers to interpret information extracted from large data sets, while humans remain in charge of the decision process.

Artificial Intelligence, AI

AI is loosely used as an umbrella term for all cognitive technologies that enable computer systems to perform tasks normally requiring some form of human intelligence. A true AI machine would combine these different technologies in such a way that it would have augmented intelligence, surpassing humans in accuracy and insight. The individual technologies, on the other hand, that are performing tasks by simulating a specific area of human intelligence are called cognitive technologies.

Virtual Reality and Augmented Reality, VR/AR

Virtual Reality technologies are being used to create simulated environments. These technologies allow the user to experience the simulation around them – as they were part of it – not just looking in from the outside. Augmented Reality (AR) integrates digital information with live video or the user’s environment in real time to augment the video with artificially added elements or effects.

Business Process Management (Suite), BPM(S)

A business process management suite (BPMS) is a set of automated tools for designing, implementing and improving activities to accomplish a specific organizational goal. BPMS is designed to support the entire process improvement life cycle from process discovery, definition, monitoring and analysis, and through ongoing optimization. BPMS tools allow the organisations to redesign or re-engineer the whole process or set of processes and often also the related IT systems (unlike RPA which is solely using existing IT- system without changes).

Enterprise Cognitive Systems, ECS

Enterprise Cognitive Systems (ECS) are a form of cognitive computing. They are focused on action, not insight, and their intention is to assess what to do in a complex business situation. ECS makes evidence-based suggestions about how the business can achieve its goals. It does so by finding past situations similar to the current situation, and extracting the repeated actions that best influence the desired outcome.


Digital Workforce is the only company purely specialising in Intelligent Process Automation services on an industrial scale in the Nordic countries. We automate the routines of computer based knowledge work and liberate human employees’ time for more productive and important tasks. Learn more about us and our services on