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Use cases with generative AI in companies

What are the use cases with generative AI in companies? Any software is only as good as the use case that needs to be solved. More and more companies are asking themselves how you can use generative AI in the company and how you can combine the information with internal know-how. This article serves as inspiration to develop your own use cases in the company

Mastering Information Management in IT: A Strategic Approach

Discover how modern information management with “amberSearch” revolutionises efficiency for IT managers through the intelligent combination of enterprise search and AI. Gain access to decentralised systems and improve information discoverability to navigate the dynamic business world with confidence. Increase productivity and control information chaos thanks to this powerful solution.

amberAI vs Microsoft Copilot: A comparison

Our Microsoft Copilot comparison clearly shows that amberAI offers some distinct advantages over Microsoft Copilot in several key areas. With a competitive price point, amberAI enables broad accessibility to generative AI, while Copilot is burdened with higher costs. The increased data protection and clear compliance with the GDPR by amberAI underlines its responsibility and commitment to protecting customer data, in contrast to Microsoft’s less transparent approach. The cross-vendor functionality of amberAI allows for equivalent treatment of results regardless of systems, while Copilot is limited in terms of Microsoft platforms.

Private AI – Should you train Large Language Models with your own data?

Learn how private AI is changing the way we use AI models. Discover how the practice of private AI makes it possible to train algorithms using only your own data to create customised solutions for your business. Learn more about the benefits of this approach and how it helps preserve a proprietary knowledge base that your competitors cannot benefit from. Read on to understand the concept of private AI in detail and how it differs from public AI models.

Integrating modern AI systems into grown IT landscapes

Integrating modern AI systems into evolved IT landscapesThe 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 […]

What should you choose an enterprise search by?

The introduction of an enterprise search requirement no longer has to be a large and comprehensive project as it used to be, but can be much leaner nowadays. In order not to have unintentionally complex implementations or technologically outdated solutions afterwards, a careful selection of the right providers is required. In order to clearly outline the requirements, we have compiled a short list to help with the selection of an enterprise search.

Best Practices User Onboarding Enterprise Search

Over the years, we have built up expertise in the field of enterprise search and have identified recurring patterns over the course of various projects. In order to share our best practices with companies implementing enterprise search, we have written this blog article. Our learnings are mostly from onboarding with SMEs and can of course vary per company/industry. While our best practices are not universal, they are a good guide to what things to consider.

What resources does the implementation of an Enterprise Search require?

Much has changed in recent years due to a change in technology. The introduction of an enterprise search is – provided one uses standard software – not a huge project. In the following, various resources are therefore discussed and, where possible, a realistic estimate of the resources required is given.