LiteSeed
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Use Case

Privacy-safe AI data without PII

Generate statistically realistic training data that contains no real personal information — enabling AI development in regulated industries.

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The challenge

Real data is off-limits. Synthetic data is the answer.

Healthcare, finance and legal AI teams can't use real patient, customer or case data for training without extensive compliance processes. LiteSeed generates statistically realistic synthetic data that preserves the statistical properties of real data — without containing any real records.

Zero PII by design

Generated data contains no real names, addresses, IDs or other personally identifiable information.

Statistical realism

Distributions, correlations and domain patterns match real data — without the compliance risk.

GDPR and HIPAA compatible

Synthetic data generated from Blueprints — not from real records — is outside the scope of most data protection regulations.

How LiteSeed helps

Blueprint-based generation — not data synthesis

LiteSeed generates data from a statistical Blueprint — not by transforming or anonymizing real records. This means there is no re-identification risk.

  • No real records processed or stored
  • Blueprints define statistical properties, not individual records
  • No re-identification attack surface
  • Audit trail of Blueprint versions for compliance documentation

Domain-realistic synthetic data

Generate healthcare, financial and legal datasets that are statistically realistic without containing real patient or customer data.

  • Medical record schemas with realistic diagnosis distributions
  • Financial transaction data with realistic fraud patterns
  • Legal document metadata with realistic case distributions
  • Custom domain schemas via Blueprint definition

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