AI built around your problem — not the other way round
You have a specific problem: documents nobody can find, data entry that eats whole days, records nobody has time to look at. We design the AI tool that fixes it, and we plug it into the software your teams already use. Not another platform — one tool that does one thing well. We start small: one department, one process, success criteria written down before we begin. As soon as personal data is involved, the GDPR requires a written contract with the provider (Article 28): we handle that at design time, not after. If you want something that does the job on its own every day, see AI Employees.
We start from your problem, not the technology
Too many AI projects start with an impressive tool looking for something to do. That is how expensive gadgets get built.
We work the other way round. The first question is not “what can AI do?” — it is “what costs you time, errors or customers, week after week?”. Nobody can find the contract signed two years ago. Your accounts team re-typing invoices by hand. A salesperson spending the evening piecing a client’s history back together before a meeting.
Those are the situations we fix. The technology comes second — and only if it is genuinely the right answer.
What this can look like in your business
Four kinds of need come up again and again.
Finding information. An internal search engine that answers questions by citing your own documents: contracts, procedures, case histories. No more digging through the shared drive.
Getting the information out of your documents. Orders arriving by email, supplier invoices, delivery notes: the data is pulled out and pushed into your tools, with no re-typing. Your team checks and approves.
Making sense of your data. You are sitting on years of sales records, incidents or complaints. An analysis tool surfaces what nobody has time to go looking for.
Fitting into what you already have. The tool plugs into your management software, your email, your shared files. Your teams keep their habits — the tool adapts, not the other way round.
How we keep the risk under control
An AI project can drift: too broad, too vague, too dependent on one supplier. Four guardrails prevent that.
We aim deliberately small at the start. One department, one process, one type of document. Not “transforming the company”.
Success criteria written down before we begin. You know what success looks like — and what failure looks like — before committing to anything heavy.
Reversibility. If the tool vanished tomorrow, your business would carry on as before. Your data stays readable, your processes stay documented, nothing depends on a black box.
A human keeps the final say. The AI suggests; someone on your side decides. A customer letter, a price, a commitment: nothing sensitive goes out without human approval.
Your data stays your data
Where is your data hosted? Who can read it? Is it used to train models that serve other companies? These questions are settled before the first line of code — in writing.
Several options exist, depending on what you require: hosting your data in France or elsewhere in Europe, keeping it completely separate from everyone else’s, or running the whole thing on your own servers. Your documents are never used to train models available to anyone else.
If you operate in a regulated sector, or your clients are demanding about confidentiality, tell us at the first conversation: it shapes the technical choices from day one.
When AI is not the right answer
Sometimes the honest answer is: don’t.
If a simple rule or a well-built spreadsheet does the job, AI is an expensive detour. A simpler tool goes live faster and runs perfectly well without us.
If your process changes every week, or is not written down anywhere, automating it just speeds up the chaos. Stabilise the way you work first — that is sometimes our first recommendation, and it needs no AI at all.
If the underlying data does not exist, or is too unreliable to trust, no model will fix that.
And if the real goal is to “do AI” for appearances, we will tell you so. You will save yourself a project.
Frequently asked questions
- How long does it take?
- It depends on what you want to tackle, and we will not promise a timeline before seeing your context. What we do commit to: a deliberately small first piece of work, a schedule set down in writing before we start, and a checkpoint where you decide whether to continue or stop.
- Who runs the tool after you leave?
- Your team, if that is what you want. The tool is documented, explained and handed over so you do not depend on us. If you would rather delegate the upkeep, our ongoing-support offer, Cap Continu, exists for that — but it is a choice, never an obligation.
- What if it doesn’t work?
- That is planned for from day one. Success criteria are written down before launch: if the tool does not meet them, we say so, fix it or stop. Reversibility is part of the deal — you get your previous way of working back, plus a clear view of what the obstacle really is.
- Will my data be used to train models for others?
- No. Your documents and data stay with you, kept apart from any other company’s, and that commitment is in writing. Hosting is chosen with you — Europe, France, or your own servers, depending on how strict your confidentiality requirements are.
- Do we need to be near Paris to work with you?
- No. Our office is in Paris and we meet there by appointment, but we work across the whole of France, on site or remotely depending on the project.
Read next
- AI in a small or mid-sized company: where to startYour first AI project does not start with a tool. How to spot a good use case, what to check beforehand, and when it is better to wait a little longer.
- Getting an AI to answer from your internal documents: what it delivers, what it demandsLetting an AI answer questions from your company’s internal documents: how RAG works in plain terms, what makes it succeed, the pitfalls — and when it is not worth doing.
- How to choose an AI provider: the questions to ask before you signTwo or three AI proposals on the table and no way to tell them apart? What a serious proposal always contains, who owns the code, and the warning signs to heed.
- An AI employee does the work. Not just the talking.An AI employee takes a task end to end: watching, sorting, drafting, following up. What to delegate, what not to, and the guardrails. Paris, France.
Start with a conversation
Tell us about the problem that costs you the most time. We will tell you honestly whether AI is a good answer — and if it is not, you will know that too. No commitment, no jargon.
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