Topic overview
All articles on AI technology and integration
Every amber article on how AI connects to systems and company data and what is behind it.
This page lists every amber article on the technology behind enterprise AI. The first group shows how AI connects to your systems through interfaces and protocols. The second explains how AI gets context and company data, the third covers the basics of generative AI, up to writing good prompts. Each card links straight to the article. If you are new to the topic, start with the intro article.
Start here: MCP explained simply: how AI connects your tools · At amber: all integrations and the data layer
On this page: Interfaces · Context and data · Basics
Interfaces and integration
How AI works with your systems through MCP, APIs and database connections.
Start here
MCP explained simply: how AI connects your tools in your company
The place to start: how the Model Context Protocol works, where it automates workflows and what to watch for on security.
Which systems amber connects, from SharePoint and Confluence to Jira, and through which channels.
4 drawbacks of MCP: where the protocol reaches its limits
Relevance, permissions, cost and knowledge questions: what to know before you rely on MCP.
Text-to-SQL with AI: connecting your database to AI
How to query a SQL database in natural language and visualize the results right away.
Best practices from 5 years of AI integration in midsize companies
Why AI is not just an IT project and how to start with everyday challenges.
Integrating modern AI systems into established IT landscapes
Five challenges in rolling out AI systems and how enterprise search and generative AI address them.
Context and company data for AI
How RAG, a context layer and knowledge graphs make AI work with your knowledge.
Overview
Understanding retrieval augmented generation (RAG)
How RAG combines search and a language model and what sets it apart from a plain LLM setup.
How the data layer connects your business data to AI while keeping existing permissions.
LLMs and knowledge graphs in knowledge management
The pros and cons of both technologies when you want to make company knowledge accessible.
What is unstructured data? Types of data explained
Unstructured, semi-structured and structured data compared, with the typical challenges.
Contextual RAG: why AI needs a context layer
Where classic RAG falls short and how a context layer makes company knowledge usable.
Combining generative AI with in-house data
How to connect generative AI with your company data without uploading everything, and which model to choose.
Born to Transform: insights from unstructured data
Co-founder Bastian Maiworm in the Fujitsu series Born to Transform on handling unstructured data.
Basics and everyday use of AI
What generative AI is, which technology it needs and how to get better results.
Prompting: how companies get the most out of AI
Which prompt types exist, what makes a good prompt and which mistakes to avoid.
12 examples of generative AI in companies
Twelve examples from search, R&D, customer service, product development and marketing.
The generative AI stack: what you need to get started
Which building blocks the stack includes and how to put it in place in your company.
What is generative AI? Combining technology with existing data
How generative AI works, where companies use it and how it helps break down data silos.
NLP explained: what is natural language processing?
In short: how AI processes human language.
Generative AI use cases in companies
General use cases and how to define your own for your company.
Deep learning vs. machine learning: the differences
What each technology does, how they differ and where they are used.
More topics
The other topic overviews, the blog and our customer projects.
How search inside a company works, how to choose and roll out a solution, plus tips for SharePoint, Confluence and Outlook.
How companies capture, share and find their knowledge, from the guide to software and AI.
What AI agents and AI assistants can do, how to roll them out and which alternatives to Microsoft Copilot exist.
Data protection, the AI Act and strategy, plus help with the rollout and with comparing vendors.
All articles by date, with search and a category filter.
Customer stories and industry solutions: how companies use amber in their daily work.