With their “Agent-Native Commerce” concept, Mirakl and OpenAI are defining a revolutionary approach that goes far beyond traditional chatbots. The autonomous AI agents actively take on tasks and relieve your team of time-consuming manual processes in e-commerce.
AI Articles & Tutorials

Our tutorials show step by step how to use AI technologies — from prompt engineering to AI programming and the use of smart tools for automation
Google Skills: Learning platform for data & AI – with gamification
📖 This article is part of our Google Gemini guide. Read the full guide →
Google Skills is a free learning platform with over 3,000 AI courses, certificates and labs. The new platform makes practice-oriented AI learning easier and directly links course completion with attractive job opportunities.
Microsoft Foundry – The new AI platform in Azure
Azure AI Foundry is now Microsoft Foundry. Microsoft is thus positioning itself more broadly, as Foundry can also manage AI models outside of Azure and Azure models can be used in all environments.
Gemini 3 Pro explained: functions, performance & innovations of the Google AI model 2025
Gemini 3 Pro redefines the boundaries of artificial intelligence in 2025 – with multimodal processing, a huge context window and human-like reasoning capabilities. This concise summary shows you the most important aspects of Google’s new AI flagship.
Implementing RAG systems: From theory to productive AI application in 30 days
TL;DR
RAG (Retrieval-Augmented Generation) connects LLMs to your own data, reducing hallucinations and enabling AI to answer questions about private documents.
- Core concept: Retrieve relevant chunks from a vector database → feed them to the LLM as context
- Key components: Embedding model + Vector DB (Pinecone, Weaviate) + LLM (GPT-4, Claude)
- Best for: Company knowledge bases, customer support, document Q&A, legal/medical research
- Typical stack: LangChain or LlamaIndex + OpenAI Embeddings + Pinecone
Bottom Line: RAG is the most practical way to make AI useful with your own data. Start with a simple prototype, then optimize retrieval quality.
You don’t just want to understand RAG systems, you want to implement them ready for production? This guide will take you from data strategy to live operation in 30 days – with concrete costs, proven tool decisions and a real case study from the SME sector.
Azure: Hosting AI models in compliance with GDPR
With Azure AI Foundry, companies can operate modern AI models such as GPT-4.1 in their own Azure region – fully GDPR-compliant and with full control over data residency, security and governance. A step-by-step guide with Azure AI Foundry
AI tokenomics explained: What do Claude, GPT-4 and Gemini really cost per million tokens?
This article provides a detailed insight into the cost structure of leading AI models and shows how you can save significant costs through strategic model selection and prompt optimization without sacrificing quality.
ChatGPT Atlas: Functions, application & comparison of the new OpenAI platform
ChatGPT Atlas revolutionizes the web experience as a full-fledged AI browser through seamless AI integration. Unlike traditional AI tools, Atlas connects intelligent conversation directly to your browsing behavior and automates complex tasks with persistent memory.
Sora 2 at a glance – functions, possible uses & risks
- Near-photorealistic video up to 60 seconds from a text prompt: Sora 2’s physics engine eliminates the morphing and teleportation artifacts common in competing tools, producing natural movement sequences and fluid dynamics that hold up to scrutiny.
- Integrated audio is the real differentiator: Unlike Runway Gen-3 or Pika Labs, Sora 2 generates synchronized background sounds, dialogue, and lip movements in a single step — no separate audio pipeline required.
- The Cameo feature unlocks real people in AI scenes: After a short video recording, any person can be realistically placed into any generated environment with full control over appearance and voice — a capability currently unique to Sora 2.
- Cost savings are real, but legal risk is significant: Production costs drop from €15,000–€25,000 to ~€500–€800, but explicit consent for every person depicted and mandatory AI content labeling are legal requirements that must be managed carefully.
Sora 2 revolutionizes AI video generation with hyper-realistic videos with synchronized audio and drastically reduced production effort. The following points show what makes the tool so groundbreaking and what you should pay attention to when using it.
Data tables in n8n – Create CRMs and databases directly in n8n
With Data Tables, n8n brings directly integrated, extremely high-performance storage to automation workflows – independent of external services such as Google Sheets or traditional databases. The feature offers advantages in terms of speed, flexibility and simple management for team and AI processes.