TRUST · TRACEABILITY & REGULATION
10 million simulated people.Zero real people exposed.
Our synthetic people and synthetic societies do not exist.
They have no real identity, customer account or personal file.
Simulation therefore does not require building a database of millions of real people.
Simulate humans without exposing humans.
THE SHIFT
A synthetic population is not a database of people.
We do not recruit ten million real respondents. We generate fictional individuals within statistically coherent populations.
For the simulated people, there is therefore no real identity to protect, no individual consent to collect, and no access or erasure request to process.
There is no real person behind a synthetic response.
Simulation can therefore involve millions of individuals without creating exposure for millions of real individuals.
REAL VS SYNTHETIC
Remove a large part of the constraint at the source.
REAL POPULATION
- Recruitment
- Consent
- Personal data
- Retention periods
- Access requests
- Erasure requests
- Reuse restrictions
- Risk of exposing identifiable individuals
SYNTHETIC POPULATION
- Fictional people
- No identifying data about the simulated people
- Reusable
- Queryable at will
- Multiple scenarios
- Millions of individuals
- No real person exposed by the simulation
The difference is not only regulatory. It is operational.
THE BENEFIT
Compliance stops slowing down experimentation.
A new scenario?
Test it.
A new question?
Ask it.
A new segmentation?
Build it.
A new population?
Generate it.
- No new recruitment.
- No new collection of identifying data.
- No new exposure of real people.
You can multiply the tests without multiplying the people exposed.
THE LIMIT
Synthetic does not mean governance-free.
The simulated people are fictional. This does not mean that every piece of data entering a project is automatically outside regulation.
If real personal data is used to calibrate or enrich a project, it remains subject to the applicable rules.
Obligations related to artificial intelligence, security, business use cases and regulated sectors may also continue to apply.
The difference is that the simulation itself does not require processing personal data about the millions of simulated people.
WHAT REMAINS, WE TRACE
Remove unnecessary risk. Audit what matters.
The synthetic layer reduces exposure to personal data about the simulated people. Traceability then makes it possible to understand how each result was produced.
We remove a large part of the problem at the source. And for what remains, we are auditable.
REGULATED SECTORS
Easier to experiment. Still governable.
Banking. Insurance. Healthcare. Public sector. Telecommunications. Energy.
The most constrained sectors are precisely those that need to experiment without unnecessarily creating new risks for real people.
Test more. Expose less.
Synthetic people make exploration possible. Traceability makes it demonstrable.
Your next decision
Which decision do you want to explore?
Describe your need. We can point you to the right level of support.
