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:
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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Data harmonisation after company mergers: How amberSearch helps the ENTECCOgroup
When companies join forces to grow together, this often leads to various challenges. Find out now how the ENTECCOgroup overcomes these challenges with amberSearch.
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!
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 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!
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
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.
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.
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.
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).