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.
You are in category
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).
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
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.
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 In order not to have unintentionally complex implementations or technologically outdated solutions afterwards, a careful selection of the right providers is required.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.
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 technical steps have to be done to implement an enterprise search? You can find it here.
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.
An Enterprise Search is a software that enables employees to easily find company internal information. Read more about the technical challenges and use cases of an enterprise search
Internal research for information draws more information than most people in a company realise. This blog article provides support to calculate the case for your own company.
Enterprise software can be installed either on-premise or in the cloud. This article explains what consequences this has. In order to understand the added value of the respective solution, you first need to know what exactly is hidden behind the two options.
According to a Statista survey, 82% of all companies surveyed in 2020 said they were already using either private or public cloud solutions. As the current trend is for more and more software solutions to be offered in the cloud, this article takes a closer look at the advantages and disadvantages of cloud and on-premise solutions.
In companies, more and more employees are sitting at their computers and becoming so-called knowledge workers. These are employees who generate added value not through physical work, but through intellectual work. For these employees, it is elementary to be able to access the company’s know-how quickly and efficiently in order to generate corresponding added value.
Every employee knows how much time they waste every day researching internal information. In management, this is a topic that is only noticed to a limited extent – the employees are there anyway. Yet virtually every employee asks himself the following questions when looking for internal information:
1. Where should I start looking?
2. Which wording can I use best?
3. Whom can I ask for support?
Every year, the applied.ai initiative, as part of UnternehmerTUM, honors the most promising German Start Ups through several partners. For this purpose, applied.ai has teamed up with strong partners such as innovators and enablers to evaluate the German start up landscape. This jury includes NVIDIA, Google and nine venture capitalists: (Digital+ Partners, Earlybird Capital, eCAPITAL, High-Tech Founder Funds, HV Holtzbrinck Ventures, Lakestar, UVC, La Famiglia and Asgard).