Integrating modern AI systems into grown IT landscapes

Integrating modern AI systems into evolved IT landscapes
The integration of modern AI systems into evolved IT landscapes is a challenge that many companies are dealing with today. The development of artificial intelligence is progressing ever faster. German SMEs in particular have to make sure they don’t miss the boat when it comes to digitalisation. There is a lack of specific know-how and experience with the various types of artificial intelligence, such as natural language processing.

But there are German solutions that help SMEs to jointly build up the know-how they need to survive on the market in the future. We would therefore like to make the necessary knowledge available to interested companies on our blog. Before thinking about the use of generative AI, you should have a rough understanding of this technology and know which use cases you want to solve with it. Only then, in our view, does it make sense to take a closer look at the introduction and requirements of such a technology.

The status quo

IT landscapes have grown continuously over the years and no one knows how much growth will accelerate in the coming years. Now, with the addition of generative AI, the growth of data volumes will increase X-fold.

In addition to the transformation from on-premise systems to fully managed systems, it is important to use the data and make important decisions from it. A key challenge is to effectively use the multitude of data sources and optimise business processes and decision-making with the help of artificial intelligence.

Many companies are still at the beginning of their AI initiatives and have difficulties finding the right approaches to introduce AI solutions. This is especially true for organisations that have had little exposure to AI or have limited technical resources.

However, solutions have been developed in the German AI landscape that support SMEs to successfully enter the AI space. Through targeted cooperation, the exchange of best practices and the provision of qualified AI experts, companies can expand their know-how, optimise the capacities of their IT infrastructure and improve their market opportunities.

5 Challenges in implementing AI systems

Some of the key challenges in integrating AI systems into legacy IT infrastructures include:

1. Unstructured data: Many companies have large amounts of data that is unsorted and unstructured. This makes it difficult to use AI-based solutions that rely on structured data depending on the use case. However, there are also AI systems that can cope with unstructured data.
2. Existing access rights: Already in the implementation of AI systems, the existing access rights in the IT infrastructure must be taken into account in order to comply with data protection guidelines and requirements, depending on the application.
3. Data silos: In grown IT infrastructures, there are often several data silos that make it difficult to access relevant information and make the integration of artificial intelligence more difficult. As a result, the data is also all in different formats and difficult to use in a uniform way.
4. Integration of old and new worlds: Companies have to deal with the question of how to connect their existing IT infrastructure with new AI-based solutions, especially if some applications and data sets are used on-premise.
5. Limited opportunities to train own AI models: It is often difficult or impossible for companies to retrain AI models themselves, as this requires high costs, extensive resources and specialised know-how. In addition, the data set is often limited and can therefore only be used to a limited extent, true to the motto: “Shit in, shit out“.

Our goal: Achieving added value through AI

At amberSearch, our mission is to help companies with limited resources to better manage the information in their unstructured data. Therefore, we have set ourselves the goal of breaking down data silos with the help of an enterprise search and making the information accessible in one place. The advantage of an enterprise search is that we do not try to break up the data sources, which have their raison d’être, but integrate them better into the existing IT landscape to avoid media breaks.

The use of AI systems in heterogeneous IT infrastructures offers enormous added value for companies – such as possible time savings or better decisions. However, depending on the company, the added values can vary from a better employee experience, increased efficiency or even less data waste.

One of the key successes of our solution is the specially trained AI model that we use to make internal company information quickly and efficiently findable. We deliberately rely on generally trained AI models, because when we trained our AI model (the first version of which was open-sourced, by the way), we found that otherwise we would be training an expert idiot who simply doesn’t perform well in the majority of internal company questions. The expertise ultimately comes from the know-how of the information that the system is supposed to process.

Solution: Enterprise Search and generative AI

A phenomenon that has been with us since the end of 2022 and will have a lasting impact on the business world is generative AI. However, in order to be able to use it in the company, it must be based on the right information.

For this reason, we combine amberSearch with generative AI. The result is amberAI. The advantage of amberAI is the combination with enterprise search. Where companies without amberSearch have difficulties in providing the right context to the generating model, amberSearch takes care of this for us.

If a user wants a text generated with specific know-how of the company, amberSearch searches out the relevant information in a fraction of a second. This is of course searched out taking into account the access rights and can then be used by the generating model to answer the user’s question and taking into account all DSGVO-relevant specifications. This technique is called Retrieval Augmented Generation.

Various companies are already using amberSearch to take their own business to the next level together with German and DSGVO-compliant providers.

We would be happy to help you realise the added value of modern technologies in the aforementioned use cases! Contact us now or try out amberSearch directly: