Safe Seed generates relation-preserving datasets for regulated sandboxes, demos, and analytics. Correlations, multi-table integrity, and measurable privacy — so workflows and QA see the structure that actually matters.
PHI, PII, and sensitive customer records are locked away from sandboxes, QA, demos, and analytics. Classic generators optimize for column-level realism and break the relationships that make data useful.
Correlations, distributions, and multi-table relationships stay intact — not shuffled columns that fail in workflows.
Measurable privacy evidence with PASS / WARN / FAIL reporting — assurance compliance teams can sign off on.
Durable jobs, config hashing, and downloadable evidence packs for retention and offline review.
PII columns masked while preserving stable, usable join keys. Per-run privacy metrics for reviewers and legal — with role separation so inspectors don't mutate sources.
Synthesize parents first, reconstruct children with referential integrity. Locked tables pass through unchanged for mixed real/synthetic environments.
Per-relation real-vs-synthetic deltas in every report. Adaptive Keep Training warm-starts from a completed run to deepen fidelity.
Configurable NaN policies per field — null rates, imputation strategies, and missingness patterns so models see the same incomplete-data reality as production.
Seed Salesforce sandboxes, databases, and files — without sending production records into environments that shouldn't hold them.
Coherent relationships across fields and tables — so UAT, integrations, and demos don't collapse on broken joins.
Schema locks, PII flags, NaN policies, and field policies without writing synthesizer code.
Reports and evidence ZIPs that survive legal review — privacy and fidelity in the same vocabulary.