AI development and automation for French businesses

Where AI pays off for French teams

Most French companies we speak to want the same three things: fewer repeated questions landing in a mailbox, quotes and invoices that stop being retyped, and a way to search their own documents. All three are routine work for current language models, provided the answers come from your content and the data stays under control.

We start with one narrow job and measure it. A wide, vague assistant disappoints. A chatbot that answers delivery and returns questions from your own policy pages usually does not.

What we build

General method and examples are on our AI development service page.

If you are unsure which row applies, start with automation. It is the cheapest to test, and the same connections to your tools later carry a chatbot or an agent. Our AI agent vs chatbot comparison explains the difference in plain terms.

GDPR, the CNIL and AI

An AI feature is still a system that processes personal data, so GDPR applies. The CNIL, the French authority, has published guidance on AI and personal data, and we use it as a reference. Check each item below with your data protection contact or lawyer.

• Say what the tool does with names, emails and messages in your privacy notice.
• Choose provider settings and regions with data location in mind, and sign the provider's data processing terms.
• Keep personal data out of prompts when the task does not need it.
• Tell users when they are talking to an AI system. The EU AI Act contains transparency duties of this kind, and the dates that apply to you are worth checking.
• Keep a person in the loop for decisions that affect someone's rights, such as credit, hiring or access to a service.

Our AI use policy template is a starting point for the internal side.

French-language quality

Current models write fluent French, but fluent is not the same as correct for your business. Tone matters: «vous» for most customers, «tu» only if your brand already speaks that way. Product names, legal terms and abbreviations such as TTC, HT or SIRET need to be used the way your team uses them. We test with real French questions, including typos and short, informal messages, before any chatbot goes live.

Two other French habits are worth designing for. Customers write long, polite messages that bury the question in the third sentence, and they expect an answer that acknowledges the greeting. And many requests mention a SIRET number, an order reference or a postcode that the system should read correctly. We build these cases into the test list so the first week after launch is not the first time anyone sees them.

How a project runs remotely

1. Pick the jobA short call settles one workflow and what success looks like.
2. PrototypeA working version on your content within the first weeks, shown in a demo.
3. Test in FrenchA list of real questions, scored by someone on your side who knows the answers.
4. Launch and monitorLogging, a review routine and a clear way for users to reach a human.

France is 3.5 to 4.5 hours behind India, so calls at 10:00 or 11:00 in Paris fall inside our afternoon. You work with one lead, and calls are booked in your working hours.

Inside each phase you see progress in a shared channel, not only on call days, so questions about wording or data can be settled in a few messages.

Pricing guidance

Projects start at $1,500, and our rate is $30 an hour. Cost depends on how many systems the AI must read from or write to, how much testing the use case needs, and whether you want it embedded on your website or run from a back office. Model usage fees are paid to the provider and are separate. See the AI chatbot cost guide and the AI automation cost guide.