What is the right technology for knowledge management in your company? Find out now about the advantages and disadvantages of LLMs and knowledge graphs.
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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Enterprise Search
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!
7 tips for defining and implementing an AI strategy for companies
This blog post uses our best practices to explain to companies which aspects a sustainable AI strategy requires.
5 steps to digitise analogue knowledge: Our best practices
This blog article explains 5 simple steps to digitise analogue expert knowledge from the minds of employees.
Defining a digital strategy | Best practices – What should companies look out for?
Today’s companies need a digital strategy. Find out now what the best practices are for creating one.
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.
Keyword-based vs Federated vs Intelligent Search – different enterprise search technologies explained
The techniques used to search for internal company information have developed continuously in recent years. The main techniques are federated search, keyword-based search and intelligent search based on large language models. This article explains and compares the various techniques.
If you want a basic understanding of the various technologies, this is the right place for you.
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).