Insurance & brokerage

AI for brokers, without exposing your clients’ health

Save hours on comparisons, written recommendations and claims, yes, but never at the price of a client file in an AI with no guarantees.

Your reality

Independent broker, general agent, claims handler or agency advisor: the day goes to comparisons, proposals, document chasing and claim filings, while the actual advice waits. And the documents AI could digest (health questionnaires, pension certificates, financial situations, expert reports) are precisely sensitive data that a consumer AI without a data processing agreement must never see.

The point is not to ban AI, your staff already use it for letters and summaries, but to frame it the way you frame the duty to advise: who uses it, on which data, with which checks.

What this costs you
  • Hours lost to comparisons, document chasing and repetitive letters
  • Health questionnaires and pension certificates pasted into AI tools without a data processing agreement
  • Duty-to-advise records written in haste, fragile at the first dispute
  • Incomplete claim filings, benefits delayed or contested
The Palambur Method in action

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 a workshop, we adapt these prompts to your real portfolio, safeguards included: no health data, no pension certificate, no identifying file goes into a public AI.

Prompt Chaptal

Recommandation écrite · ce que vous proposez et pourquoi

Your proposal and its reasons in black and white, the record that holds the day a client disputes it.

See it in Chaptal →
Prompt Chaptal

Déclaration de sinistre · complet, daté, sans un mot de trop

A complete filing the first time, without the extra sentence that invites a refusal.

See it in Chaptal →
Prompt Chaptal

Revue annuelle · ce qui a changé chez le client depuis douze mois

A tour of what changed for the client, prepared before the meeting rather than discovered during it.

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.

Where to start
Training

« Le Collaborateur, augmenté »

Your advisors learn to frame AI on their real client files, safeguards included.

See the training →
Audit & advisory

AI usage audit

An inventory of the AI usage already present in your agency, and the framework to hold it.

See audit & advisory →
F.A.Q.

Foire aux questions

Can I paste a health questionnaire or a client file into a consumer AI?

No: health data is sensitive data under the nLPD, and what you paste can leave your control. The framing provides anonymization before anything is sent, and tools that train no public model on your content.

Can AI write my recommendations and document my duty to advise?

Yes, from your meeting notes. A framed prompt states what the recommendation must contain and what it refuses to invent · the advice and the signature stay yours.

Can AI compare coverages for me?

It prepares the comparison from the documents you hand it, in the format you impose. It replaces neither reading the general conditions nor your judgment · a framed prompt refuses to assert what the contract does not say.

What does the nLPD change for a broker or an agency?

It requires knowing who processes which insured persons’ data, where and for how long · subcontractors included. A use case in the sheet walks through exactly that inventory, from data access to retention.

Should the whole agency be trained, or just the advisors?

Usage appears everywhere, from the front desk to claims handling. A common base for the agency, then deeper work for those who advise, holds better than isolated expertise.

Next step

Talk about your portfolio