Successful completion of the innovation and research project KI.RPA
in R&D | Press

Successful completion of the innovation and research project KI.RPA

Unique combination of Artificial Intelligence, Robotic Process Automation and Process Mining

Darmstadt, September 08, 2021 - The Process Analytics Factory (PAF) successfully completes the innovation and research project KI.RPA. The BMBF-funded research project combines Artificial Intelligence (AI), Robotic Process Automation (RPA) and Process Mining in a so far unique combination. KI.RPA dealt with the automation of complex and less structured tasks by software robots.

KI.RPA is a joint project under consortium leader Servicetrace GmbH, a monitoring software specialist contributing its expertise in process optimization and robotics, Process Analytics Factory GmbH (PAF) as a specialist and provider for Process Mining with the Process Mining solution PAFnow integrated in Microsoft Power BI, the non-profit August Wilhelm Scheer Institute for Digital Products and Processes (AWSi), which contributes its expertise as a research service provider, the Telecooperation Laboratory (TK) of the Technical University of Darmstadt, which investigates the practical benefits of Process Mining methods, and application partner Deutsche Telekom Service GmbH (DTS).

Due to digitalization, cost savings and higher customer and flexibility requirements, companies are faced with the challenge of using their existing resources more efficiently. In addition to technological innovation, the aim of the project was to serve these needs by means of process automation through software robotics and, at the same time, to realize the basis for future-oriented human-machine interaction.

The potential behind this is enormous: a software robot can relieve up to five employees of repetitive processes, allowing humans to devote themselves to work that requires their individual experience and decision-making skills.

Currently, however, the required configuration of software robots still involves considerable manual effort - because first the business process must be modeled at least once by a domain expert and the necessary process knowledge must be entered manually into the system; only then can the software robot be configured on the basis of clear execution rules.

Tobias Rother, CEO of Process Analytics Factory, said on the occasion of the project completion: “Robotic Process Automation is a key optimization technology for efficient, error-free and transparent business processes. However, a large proportion of current Robotic Process Automation projects fail or are terminated prematurely because it is unclear which processes can really be automated well. Previous tools often focus only on automating well-structured tasks that are particularly easy to capture and automate. This falls far short of exploiting the potential of this key technology. This is exactly where KI.RPA comes in!"

Through the combined use of AI, RPA and process mining, KI.RPA has succeeded in accelerating numerous steps in automation projects. These include, for example, the identification of routine tasks and their automation potential, automatic decision-making in the case of branched processes, and the assignment of tasks to suitable employees if the automation of a process instance is not feasible.

Dr. Alexander Seeliger, Chief Scientist of PAF, expects a high added value for RPA users by integrating the project results into future PAFnow versions: “With the completion of KI.RPA, PAF strengthens its competencies in the areas of Robotic Process Automation and Artificial Intelligence. We now know even better where automation via software robots is worthwhile and can use them much more frequently. It can be seen in advance whether certain process flows are suitable for automation at all. Above all, however, complex recurring tasks in processes can in future be easily automated for the first time with the developed AI technologies."

In the Process Mining market, PAF holds a leading international position in innovation research and is considered a prime example of successful innovation policy in the fields of Artificial Process Intelligence and Process Mining. KI.RPA is already the fifth successfully completed research project of PAF, which was funded by the BMBF and the state of Hesse.

Within the framework of this practice-oriented innovation research in cooperation with leading research institutes and industry partners, prototypes in the fields of Artificial Intelligence, Predictive Analytics, Industry 4.0, Blockchain and RPA are transferred into patentable software solutions.

For more information on KI.RPA, visit the project partners at:

Servicetrace GmbH: https://www.servicetrace.de/robotic-process-automation/

AWSI gGmbH: https://www.aws-institut.de/ki-rpa/

Process Analytics Factory GmbH: https://pafnow.com/research/

Telekooperation Lab: https://www.tk.informatik.tu-darmstadt.de/

The project is partly funded by the German Federal Ministry of Education and Research (BMBF), funding line KMU-innovativ: Informations- und Kommunikationstechnologien.