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Sustainability and environmental protection are topics that are now part of our daily lives. The UN’s 17 Sustainable Development Goals have been designated by Germany’s current federal government as a guideline for political action. If we want to truly understand environmental problems, systematically analyse them and take action against them using IT systems, we must draw on our most crucial tool: environmental data. In my blog post, I’ll give you an overview of the possible ways to apply artificial intelligence (AI) to the field of environmental protection.

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Industries

22.02.2022 By Tim Strohschneider

Identifying customers’ needs before they have them

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If we know what our customers will want tomorrow, we can make them the perfect offer today. Unfortunately, this is rarely successful, and products are usually just ‘dumped’ on thousands of people at a time. In my blog post, I will explain how the next-best-action approach can help banks anticipate the needs of customers and the next steps that would be best for them.

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Industries

Whether it arrives on paper or as a PDF, vast amounts of information reach our banks via the documents they receive (digital or analogue). In order to make this information usable for further processing in digital processes, the relevant information must be read out correctly and passed on to the right place in the process. This blog post is about how we can reliably perform this process and others for our customers using text extraction.

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Industries

At the beginning of the global pandemic, the switch to mobile working was another wake-up call for many companies to invest more in digitalisation. A complete integration of all company processes into a few central systems often requires very high investments and can rarely be realised in a short amount of time. One possible solution to this situation is robotic process automation (or RPA). We explain what this is all about in our blog post.

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AI

14.07.2021 By Matthias Proschinger and Dr. Zeljko Dzunic

Low code and AI: the next big step in the AI adoption strategy – part 2

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The field of artificial intelligence (AI) is arguably the biggest technological driver of the future, but projects often fail due to the complexity of their implementation or a lack of experts. In the first part of this series, we tried to answer the question of how low-code platforms can facilitate AI adoption. In this part, we will now take look at intelligent process automation – a combination of different technologies: artificial Intelligence, low code and robotic process automation (RPA). What are the advantages of using this combination? Using a well-known use case with SAP, we will introduce you to the advantages of intelligent process automation to optimise workflows.

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AI

To ensure that AI initiatives don’t fall short of their objectives, insurance providers need to take a holistic approach that also includes people – both customers and employees. As I’ve mentioned in a few of my previous blog posts, there are quite a number of challenges involved in deploying AI-based systems. This blog post deals with the specifics of the approach and how it differs from traditional projects. I will not go into regulatory aspects in this post.

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Methodology

Is personalisation on the Internet a topic of the future? Actually, it’s already a major topic now and is set to become even more important in the future! In this blog post, I will describe how you can profit from AI-powered personal communication and set your business and its products and services apart from the competition.

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AI

02.06.2021 By Matthias Proschinger and Dr. Zeljko Dzunic

Low code and AI: the next big step in the AI adoption strategy – part 1

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The field of artificial intelligence is arguably the biggest technological driver of the future, but projects often fail due to the complexity of their implementation or a lack of experts. In the first part of this blog series, we take a look at how low-code platforms as a disruptive innovation in software development can make adopting AI easier and show you two use cases to demonstrate how this technology is contributing to the ‘democratisation of AI’.

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