Enterprise search is necessary to integrate AI into company processes in the long term. This article explains the role of enterprise search.
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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amberAI
What is a multi-agent system?
Multi-agent systems are the logical development of classic AI agents. You can find out what these systems can do and what their purpose is in this blog article.
DB Regio AG – Revolutionising customer service together
On 6 September 2023, amberSearch was invited to Station Berlin to present a solution on how to automate customer dialogue with the help of generative AI at the Zukunft Nahverkehr trade fair as part of the DB mindbox Accelerator. This pitch was won by amberSearch. Here is a recording of the pitch:
What is generative AI: knowledge transfer through the intelligent combination of technology and existing data silos
Use generative AI to break down internal data silos. Find out how it works with an AI search here!
Alternatives to Microsoft’s Copilot
How can generative AI be used across systems and why are the systems of other providers not suitable for this?
AI in knowledge management – 5 decisive factors that artificial intelligence is changing for companies
Wondering what impact AI will have on your company’s knowledge management? We explain how you can use AI in knowledge management!
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
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!
What is generative Multi-Hop Q&A?
Multi-hop question answering (multi-hop Q&A) is a method for generating better quality answers in the field of generative AI applications. As a further expansion stage of a Retrieval Augmented Generation (RAG) system, the aim is to consider all aspects of the prompt as far as possible before an answer is generated. This blog article explains this technique.
How to Ensure Successful Generative AI Integration in Your Company
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.
One copilot to rule them all
In the future, intelligent AI assistants will make our everyday work easier in certain situations. However, it is important to have the right co-pilot in use, namely one that works across all systems. The problem with most assistance system providers is that the assistance is limited exclusively to their own systems. This blog article shows how it can be done better.
Understanding Retrieval Augmented Generation: A New Frontier in AI
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.