Guide · Artificial intelligence
Artificial intelligence for businesses: the guide
I have been writing about AI since 2023 with a practical angle: what really works, what it costs and how it fits into a small business’s processes. Here you will find every article in one ordered path, from the basic concepts to projects in production.
Where to start
Three reads to get a clear picture
RAG: How to Build a Chatbot That Actually Knows Your Company
How to build an assistant that answers questions on your company’s documents and cites the source. The AI project SMEs ask for most.
Business Automation with AI 2026: n8n vs Make.com – The Definitive Guide to Transform Your Processes
A comparison of the two most popular platforms for automating processes with AI, with costs and real examples.
NLP & Large Language Models 2026: From Theory to Practical Applications – Complete Developer Guide
What Large Language Models are, how they work and where they apply: the foundation for everything else.
AI in business processes
Chatbots, automation, feedback and document analysis: these are the cases where AI pays for itself within months. For each one I cover tools, limits and costs.
- RAG: How to Build a Chatbot That Actually Knows Your Company
- Sentiment Analysis & Topic Modeling: What Your Customers Really Mean
- Multimodal AI: Analyze PDFs, Images and Documents with Claude, GPT-4 and Gemini
- Business Automation with AI 2026: n8n vs Make.com – The Definitive Guide to Transform Your Processes
- How to Create an AI Agent with n8n: The Definitive 2025 Guide
- Voiceflow: Build an AI Chatbot Without Writing Code
- WP Publisher: Automate WordPress Articles with Claude AI
- AI: create a chatbot with your own data
- Conversational AI in Retail: benefits and how to implement it
- Conversational AI in Retail: Use Cases
- Artificial Intelligence in Marketing
- Artificial intelligence tools that will improve your SEO [part 1]
- Artificial intelligence tools that will improve your SEO [part 2]
- Artificial intelligence in the agri-food sector [part 1]
- Artificial intelligence in the agri-food sector [part 2]
LLMs, NLP and prompt engineering
How language models reason, how to write prompts that reduce errors and how to connect them to company data with knowledge graphs and agents.
- NLP & Large Language Models 2026: From Theory to Practical Applications – Complete Developer Guide
- What is LangGraph?
- Knowledge Graphs and Large Language Models (LLMs) Together [part 1]
- Knowledge Graphs and Large Language Models (LLMs) Together [part 2].
- NLP: a comprehensive guide [Part 1]
- NLP: a comprehensive guide [Part 2]
- NLP: a comprehensive guide [Part 3]
- Prompt engineering
- LLM: Prompt Examples
- Prompt engineering: prompting techniques [part 1]
- Prompt engineering: prompting techniques [part 2]
- AI: the best prompt techniques for leveraging LLMs
- AI: prompt engineering to reduce hallucinations [part 1]
- AI: engineering prompts to reduce hallucinations [part 2]
- AI humanizers explained: What they are and why they matter
Computer vision
Object detection, segmentation and cloud services for image and video analysis, and the industries where they make a difference.
- Computer vision and artificial intelligence
- Computer Vision: The 5 Sectors Where It Makes a Difference
- Computer Vision 2026 (Part 1/3): YOLO and Real-Time Object Detection – From Zero to Working System
- Computer Vision 2026 (Part 2/3): SAM, Cloud Services, and Business ROI – From Universal Segmentation to Real-World Applications
- Computer Vision 2026 (Part 3/3 – FINAL): Ethics, Privacy, and the Future of Visual AI – Building Responsibly
Machine learning and deep learning
The foundations behind every AI system: supervised and unsupervised learning, neural networks and clustering algorithms explained with examples.
- Deep learning: introduction
- Deep learning: key concepts
- Deep learning: Supervised learning [part 1]
- Deep learning: Supervised learning [part 2]
- Deep learning: unsupervised and reinforcement learning
- Deep learning: roots
- Deep learning: developments in the 21st century
- Deep learning: success stories
- Exploring artificial intelligence: deep learning project ideas
- Teachable Machine: Learn Machine Learning in 10 Minutes (2026 Practical Guide)
- DBSCAN: how it works
- K-Means: how it works
- Hierarchical clustering: how it works
- Clustering Techniques in the AI Era: Why They’re Still the Heart of Data Analysis
Tools and generative AI
Reviews and guides to the tools I use or get asked about most: assistants, image and video generators, vibe coding.
- Claude: What is it and how does Anthropic’s AI work?
- Claude Code + Claude Design: From Idea to Shipped Code
- ChatGPT: what it is and what the revolutionary new text generation tool can generate
- Perplexity AI: What It Is, How It Works, and Why It Revolutionizes Online and Enterprise Search
- Google NotebookLM: your new ally with AI
- OpenAI Dall-E 3: review of generative AI for images
- Google Veo for Creative Video: The New Era of Automatic Video Production
- Generative AI 2025: The Revolution Creating Content from Nothing
- AI Chatbots and Music 2026: When Artificial Intelligence Becomes Conversational and Creative
- Vibe Coding: The Revolution Turning Ideas Into Code Through Conversation
- Vibe Coding 2026: The Tools That Will Dominate the Future of Software Development
- Vibe Coding: The End of Traditional Programming?
- The Future of AI: Professions Redefining Work (2026-2035)
- Android Earthquake Alerts (AEA): Your Smartphone Detects Earthquakes
You will find every article, including the latest, in the Artificial intelligence category of the blog.
When you need help
Want to bring AI into your processes?
I start with an audit of your processes and the data you already have, identify the two or three use cases with the highest return and build them small, measuring results before scaling. Projects are AI Act compliant from day one.
Frequently asked questions
Which article should I start with?
If you want to understand what AI can do in a company, start with the RAG chatbot guide and the one on n8n and Make. If you are interested in the theory, the NLP and LLM guide is the best starting point.
Does an SME need a technical team to use AI?
No. Many projects can be built with no-code or low-code tools. You do need someone who knows the company’s data and processes, and a person who checks the results before they are used.
How much does an AI project cost for an SME?
It depends on the use case. A document assistant or an automation starts from a few thousand euros, and in Piedmont it may qualify for the Digitalisation Voucher. The audit is there to estimate costs and return before you invest.
Are the articles up to date?
I publish a new article every week. Older ones explain concepts that remain valid; for tools and prices, the most recent article on the same topic is the reference.
Got an idea for an AI project?
Tell me about it: I will tell you whether it is feasible, what it costs and where to start.