Point Syntheticore at a dataset and get back statistically faithful, privacy-safe records — on demand, at scale, through the app or the API, with utility and privacy measured on every run.
Connect a source table or file and the generator models its distributions, correlations, and constraints.
Keep keys, joins, and referential relationships intact across multiple related tables.
Every run ships a report comparing synthetic vs. real on the statistics and model performance that matter.
Membership-inference and distance-to-closest-record checks prove no source row is being memorized.
Automatically flags and handles sensitive fields so nothing personal slips through by accident.
Generate from a clean web app or wire it into your pipelines with a REST API and SDKs.
Bring a table, file, or database connection. Nothing leaves your control without your say-so.
The model captures the statistical shape of the data — including the rare and awkward parts.
Produce as many synthetic rows as you need, in the formats your tools already expect.
Review the utility and privacy report, then export or push straight into dev, test, and partner environments.
Book a walkthrough and we'll generate a synthetic version of one of your datasets — utility and privacy report included.
Request a demo →