How should a buyer check grounding and disclosure risk in a generated sample?
Because the output is generated, a buyer can test it for resemblance to real entities, ask how grounding worked and review free-text fields where identifying detail is most likely to appear.
**Is the data real?**
No. MirrorFirm's commercial output is generated and synthetic, informed by direct observation of how businesses operate. It is not a copy of real business records.
**Does that remove the need to check?**
No. Generation does not by itself establish that the output is free of resemblance to real people or organisations, and it does not amount to a privacy or regulatory approval. Treat disclosure as a risk to inspect.
**What can a buyer do?**
- Search names, identifiers, addresses and phone formats in the sample against your own reference lists. - Read free-text fields such as handover notes and case descriptions, where specific detail tends to slip in. - Ask how entities and policies were produced and what constraints applied. - Test for repetition, where the same unusual detail recurs across records. - Have your legal or privacy team review the sample under your own standards.
**Is realism a different question?**
Yes. Grounding asks whether the workflow behaviour is plausible. Disclosure asks whether the material resembles something it should not. Review both, separately.
**What should be agreed in a pilot?**
The checks you will run, the sample size you will review and what result would lead you to change the scope.
A short structured review of a sample surfaces most grounding and disclosure concerns before a lab commits to larger volumes.
- Audience:
- Model labs
- Content type:
- FAQ
- Buyer question:
- How to evaluate it
Content release: r-a220eb6e099b243b
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