03 · Resources
Business AI: private and at the right cost
Putting AI to work in a small business means picking, for each task, the cheapest model that does it well, keeping sensitive data in an environment you control, and connecting the model to your documents rather than to its training memory. Cost and confidentiality are decided at design time, not on the invoice.
Start with the guide
Integrating AI in business: private and at the right costFor teams of 20 to 500 people, integrating AI comes down to answering five questions in order: which task, where the data goes, which model, at what price, under what rules. This guide takes them one by one and points to our detailed articles.
19 articles
Practical guide11 min The topic guide
Integrating AI in business: private and at the right cost
For teams of 20 to 500 people, integrating AI comes down to answering five questions in order: which task, where the data goes, which model, at what price, under what rules. This guide takes them one by one and points to our detailed articles.
Understand10 min
Agentic AI: how an agent's loop works
An AI agent does not do everything in one go: it runs in a loop, gathers context, acts, checks and starts again. Understanding that loop means knowing where to put the controls, the limits and the human review.
Practical guide10 min
AI Act and GDPR: what an SME using AI must do
An SME that uses ChatGPT or a CRM with built-in AI already has obligations. This guide takes stock in October 2026: your role under the AI Act, the timetable revised in July 2026, what the GDPR requires and the steps to get compliant.
Practical guide10 min
An AI agent in production: from demo to product
An AI agent demo impresses quickly. Turning it into a tool a team uses every day takes an owner and written rules: what four public cases show, and what we run ourselves.
Practical guide10 min
The cost of AI in business: tokens, routing and forecasting
What you really pay when you use an AI through an API: input and output tokens, the context sent back with every call, an agent's turns. And a method to forecast the bill before you receive it.
Understand29 min
AI decision models: Jev, Clef, uses and costs
Jev, Clef and their rivals write nothing: they decide, with a probability attached. What these decision models are used for in each line of work, how to put them in place, what they really cost and what we make of them.
Stepping back8 min
Does AI use too much energy and water?
A query to a chatbot uses very little, and yet data centre consumption is expected to more than double by 2030. The two camps are talking about different scales: the verified figures, our view, and the frugality that really matters for a business.
Stepping back11 min
AI return on investment: why it is taking so long
The figure of 95% of AI projects with no return went round the world. What it really measures, why the other studies say roughly the same thing, and the practical lessons to draw from them for an SME.
Stepping back15 min
ChatGPT Pro 500: why OpenAI is moving to $500 a month
A $500 plan, a $200 plan that includes half as much, a postponed IPO: in forty days, OpenAI has upended its pricing. What changed, why, and how Anthropic, Google, xAI, Meta or Mistral could respond.
Stepping back8 min
Does AI make us dumber? What the studies say
Not all the studies doing the rounds on this subject are worth the same. We rank four of them by strength, from a field experiment to a preprint on 54 people, and say what emerges.
Practical guide12 min
Enterprise AI governance: who can access what
An AI assistant reads whatever your access rights let it read, sharing mistakes included. Here is how to split your knowledge bases by department, keep a common core and decide who writes to the shared memory.
Practical guide9 min
Evaluating an AI model before putting it into production
Public leaderboards do not tell you whether a model will do your work well. This guide gives a method for testing it on your own tasks: quantified criteria, real examples, scoring, cost, and a new test whenever the model changes.