With the application of our products and software you have the opportunity to increase your sucess. At the same time, there is an opportunity to check your processes with the software used and to automate them independently of the system. The basis for this is a well-founded and complete process analysis.

Here you can find a description of some examples of use and application.

RPA in Bank and Savings Bank

  • Data control
  • Garnishment processing
  • Account opening/change of account/account closure
  • Depot opening/change of depot/depot closure
  • Power of proxy
  • Change of delivery address
  • Exemtion order

RPA in financial accounting

  • Landing and maintenance of standing data
  • Landing of terms
  • Examination of bookings (e.g. document journal) and safeguarding of four-eyes principle
  • Execution of end-of-month accounts and annual financial statements

RPA as a Bridging Technology

Despite of increasing digitalisation and sophisticated software, repetitive, diligent but routine pieces of work are still done manually.

As a bridging technology RPA can remove annoying duties from you, and so release your employees for high-grade, creative, value-adding operations.

In particular, your established software programs do not have to be adjusted. So RPA solutions can faciliate quick wins, until a native software solution with strategical orientation can supersede the already existing programs. Among other things RPA deals with:

  • Filling out forms
  • Transfer of data from one template into another
  • Operating with software
  • Creation of tables
  • Creation of reports

Recognisation of Image Content with AI

A specific, learnable software with integrated artificial intelligence (AI) is trained by presenting defined images from a database. The software is taught to pay attention to certain parameters, such as object sizes and perspectives.If the software is confronted with new pictures that do not yet exist in the data base, it examines those for the defined specific values it is trained for. It aligns and calculates how high the likelihood is, that the object is detected correctly. Thus it teaches itself onward, and integrates these new pictures in the data base as well. So the AI is trained to achieve optimal results.

If an arbitrary picture is presented to the AI, it makes a comparison with the pictures of the data base that it is already familiar with.

If the software clearly recognizes what is shown in the picture, or a certain property on which it was trained, this is a match.This can initiate following processes or steer RPA bots.

Here we show you how this self-developed image recognition software with AI can recognize and name a wide variety of objects on images.

AI picture recognition: Office

AI picture recognition: Products

AI picture recognition: People