Business model
Sales qualification, privacy and model validation design, compliant SOW, and private environment.
MirrorFoundry separates proposed controls from proven controls, avoids automatic anonymisation claims, and defines the evidence a customer should expect before any synthetic release.
These facts describe the current product preview, go-to-market, and delivery model. They are not a claim that statutory operator disclosures or production contracting are complete.
Sales qualification, privacy and model validation design, compliant SOW, and private environment.
European operations serving regulated and data-scarce organisations.
Customer-admin invitation after implementation and acceptance; no public signup.
Every engagement should leave a reviewable chain from intended use and source scope to an accepted data or model decision.
The decision, affected groups, permitted uses, exclusions, and accountable business owner.
Approved fields, entities, relationships, sensitivity, constraints, holdout design, and retention.
Similarity, linkage, inference, memorisation, and rare-record risks to test.
Statistical, constraint, analytical, and model tasks with acceptance thresholds.
Generator configuration, privacy results, fidelity, task performance, model scenarios, and exceptions.
Named sign-off, limitations, permitted use, expiry or review date, and remaining risks.
Bring company, privacy, legal, security, and model-validation requirements into qualification so the SOW can make every obligation explicit.
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