01
Your data does not train third-party models
The architecture is set during the diagnosis: data residency in the Principality, no reuse for training, logging of every access. It is verifiable, and it goes into the contract.
Sector · Wealth management
Your managers spend more time building files than managing assets. Here is what AI really takes on in a Monegasque family office, what it must never take on, and under what conditions law n°1.565 allows it.

When a family office considers AI, the first request is almost always about reporting. It is visible, it comes back every quarter. It is also, in most houses, the best-equipped process.
Time is lost at the entry point, when onboarding a complex wealth structure. A Luxembourg holding, two trusts, a property in the Principality, a yacht under a foreign flag: for weeks, your most experienced staff collect documents, read them, cross-check them and rebuild an ownership chart by hand.
This is exactly the kind of task a well-designed AI system takes on, and the one that hides the most underestimated confidentiality risk. We develop this reasoning in our analysis the real bottleneck of a family office.
Five tasks
Our estimator’s deliberately cautious assumptions: each task is weighted by the share of staff who actually perform it.
| Task | Temps hebdomadaire | Part automatisable | Staff involved |
|---|---|---|---|
| Collecte & analyse documentaire | 7 h | 65 % | 80 % |
| AML compliance | 5 h | 60 % | 40 % |
| Reporting AMSF & consolidation | 6 h | 70 % | 25 % |
| Schedules & client follow-up | 4 h | 70 % | 70 % |
| Correspondance clients | 4 h | 55 % | 100 % |
Weekly time measured for a staff member who actually performs the task. An audit replaces these averages with your figures.
Law n°1.565
01
The architecture is set during the diagnosis: data residency in the Principality, no reuse for training, logging of every access. It is verifiable, and it goes into the contract.
02
In AML due diligence, AI prepares the file, cross-checks the documents and flags inconsistencies. The onboarding decision remains human, traced and reasoned.
03
Processing wealth data calls for an up-to-date register and, depending on the risk, an impact assessment. These outputs are part of the engagement. Our analysis of the law.
Frequently asked questions
Twelve weeks at most from immersion to production, with a prototype on your real files from week four. See the method.
No. The architecture is set during the diagnosis so that your data stays hosted in the Principality with providers established there, on a private European cloud or on your own servers. It is never used to train a third-party model, and every access is logged.
No, and we do not offer it. In AML due diligence, AI prepares the file, cross-checks the documents, flags inconsistencies and drafts a summary. The decision remains human, traced and reasoned. An AI deciding alone on a new relationship would expose you before the AMSF as well as the APDP.
A prototype runs on your real files within four weeks, and the first gains can be measured in the weeks that follow. The full cycle, from immersion to production, takes no more than twelve weeks.
No. We design, deploy and train. The tools are built for wealth managers and lawyers, not engineers. The documentation we hand over lets your teams run them without us.
An artificial intelligence and data integration project is eligible, and co-funding can reach 70% excl. VAT for eligible entities. We support you in putting the application together, in partnership with a Monaco-based provider. See our Fonds Bleu funding page.
The eight sectors
Contact
A 30-minute conversation to identify a first high-impact use case. Confidential, with a non-disclosure agreement from the first conversation.
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