Gretel.ai

Name: Gretel.ai
Author: Gretel (NVIDIA)

Generative synthetic data with differential-privacy guarantees.

Test Data & MocksFree tierAI features

What it is

Gretel trains generative models on your data to produce synthetic datasets that preserve statistical relationships while providing formal privacy guarantees, along with a quality and privacy score for each generated set. It is used where anonymisation is not considered strong enough — health, financial and regulated research data.

Best for

Regulated organisations that need shareable data with defensible privacy properties.

Where it is strong

Formal differential-privacy guarantees rather than best-effort masking.
Synthetic data preserves statistical relationships useful for analytics and model training.
Privacy and quality scores make the trade-off explicit.

Where it falls short

Model training adds time and cost compared to rule-based masking.
Overkill when simple anonymisation would satisfy the requirement.
NVIDIA acquisition changes the strategic outlook.

Pricing

Free tier available

Free tier

Free tier: Free tier with a monthly credit allowance.

What drives the bill: Consumption-based on generated records; enterprise agreements available.

Check current pricing on Gretel (NVIDIA)’s site

Figures are indicative and were last reviewed August 2026. Vendors change pricing often; confirm before you commit.

Works with

Python SDKSnowflakeBigQueryS3Databricks

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Test Data & Mocks

De-identify production data into safe, realistic, referentially intact test databases.

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