AI in customer service, without pasting mail into public AI
Faster replies and follow-ups that go out on time, yes, but never at the cost of an order or a complaint pasted into a tool with no guarantees.
Order desk clerks, account managers, sales assistants: your day runs on emails, orders and complaints. Each of those messages carries names, prices, disputes · exactly what a rushed colleague pastes into consumer AI to save a few minutes.
The point is not to ban AI: your team already uses it between two calls. The point is to give it a frame: what it may read, what it may draft, and what it never promises on your behalf.
- Hours lost to repetitive replies, follow-ups and order entry
- Orders, disputes and client details scattered across unframed AI tools
- Replies that vary from one colleague to the next, written commitments made without sign-off
- Clients lost over a mishandled complaint, not over price
See for yourself
A prompt structured in 5 blocks: Instruction · Role and audience · Data · Constraints · Format. An unframed AI invents; the frame stops it.
In the workshop we adapt these prompts to your product lines, your terms of sale and your own email templates, with one constant safeguard: the AI drafts the reply, only you commit the company.
Réponse à un email client en 5 langues (FR/DE/IT/EN/ES)
The reply goes out in the client’s language, without waiting for the colleague who speaks German.
See it in Chaptal →Traitement d’une réclamation client (chaîne complète)
From acknowledgement to commercial gesture, a steady chain of replies that defuses instead of inflaming.
See it in Chaptal →Relance de paiement en escalier (J+15, J+30, J+45)
The right tone at every step, firm without breaking the relationship, ready to send.
See it in Chaptal →30 use cases cover your line of work in the Chaptal catalog, out of 750 in the corpus · each one states what it produces, what it expects from you, and what it refuses to do.
« Le Collaborateur, augmenté »
Your teams learn to frame AI on their own emails, complaints and follow-ups, on your premises.
See the training →An audit of your AI use
A clear picture of what already flows into public AI, and the frame to keep going without exposing your clients.
See audit & advisory →Foire aux questions
Can we use AI to answer clients without exposing their data?
Yes, provided you separate what the AI reads from what identifies the client. We show how to prepare a message before handing it to a tool, and which tools offer real data processing guarantees.
Does an AI-generated reply commit the company?
Yes, from the moment it is sent, like any other written business exchange. That is why the catalog prompts impose a human review before sending · the AI drafts, your colleague decides.
Our replies go out in several languages · can AI hold the standard?
For the usual languages of the Swiss market, yes, provided you feed it your trade vocabulary and your house phrasing. The prompt fixes the terminology once and for all, and reviewing stays faster than writing.
What should we answer a client invoking the nLPD about their data?
Their request is governed by Swiss law and deserves a considered answer, within the legal deadline. A card in the catalog walks through handling the request and drafting the reply, with no improvising.
Do we really need one more tool in an already full day?
No. The method builds on the AI tools your teams already use and gives them a frame, with no extra software and no IT project.