Use generative AI to break down internal data silos. Find out how it works with an AI search here!
Generative AI and its use in the company
On our blog, you will find all the information you need on AI and its use in the company. From technical explanations and references to strategic topics, our blog highlights everything that is relevant to the use of AI in the company and contributes to decision-making.
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Decision Making
What are you waiting for – are you still searching or have you already started finding?
30 minutes a day – that’s how much time employees spend on internal searches. But you can easily save 40% or more of this time. We’ll show you how!
Why AI can partially compensate for the shortage of skilled labour
With skilled labour becoming a bigger problem in every economy, AI gives a chance on reducing the shortage. We explain, how this could be done.
AI software – make or buy when developing AI solutions for companies
Get to know the pros and cons of an AI software make-or-buy decision now.
Large language models (LLMs) and knowledge graphs for knowledge management in companies
What is the right technology for knowledge management in your company? Find out now about the advantages and disadvantages of LLMs and knowledge graphs.
Best practice incl. example: How companies define an AI use case
Learn how to define an AI use case for your own company with our best practice using a concrete example.
Identifying and prioritising AI use cases in companies
Learn how to easily identify and prioritise AI use cases with the help of 2 frameworks
New Work with AI – simply think differently!
New Work with AI enables a completely new mindset in the company. We explain what companies need to know
Questions to ask when selecting AI software for your company
Ask the right questions when selecting AI software. Here you can find out exactly which questions you need to ask!
AI introduction checklist – your guide to successfully implementing generative AI in your company
This AI introduction checklist reveals exactly what needs to be considered when introducing an AI solution!
How to introduce generative AI in companies – What should you look out for and what makes the introduction successful?
Many companies need and want to gain experience with generative AI. The introduction of generative AI is therefore on the roadmap of many companies. This blog article is about how to successfully combine in-house expertise with generative AI – within a secure and GDPR-compliant framework – and what to look out for. The introduction of generative AI is not as complex as it first appears.
Technical foundations for the introduction of generative AI in companies
Learn all the technical basics you need now if you want to use generative AI in your company.
What is Retrieval Augmented Generation and how does amberSearch use this technology?
Retrieval Augmented Generation (RAG) is an approach that enables companies to use generative AI sustainably. In this blog article, we explain what Retrieval Augmented Generation is and how we use this technique at amberSearch to get the most out of it for our customers.
Retrieval Augmented Generation is an NLP technique for enterprise search applications that solves many of the challenges faced by traditional generative Large Language Models (LLMs).
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
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.