The advanced toolkit to generate synthetic data

Generate synthetic data from single and multiple table datasets automatically

"The installation of the Statice SDK was very easy and smooth. If you are used to using a Python library, it’s basically just another library."

Lead Data Analyst, Financial institution

Seamlessly build synthetic data pipelines for better products and services

"What we looked for, and one of the reasons why we chose Statice, was the on-premise aspect of the software. Plus, it's a nice Python package that we could easily include in our data preparation or in data pipelines."

Lead Data & Innovation, Leading insurance

Tailor utility and privacy to your data operations and disclosure context

"The Statice toolkit provides quite some accurate results: out of 1000 models trained on synthetic data, 90-92% produced the same decisions."

Advanced Analytics & ML, International bank

⟶ Learn more about privacy and compliance

Toolkit features and capabilities

Our SDK was built to be flexible. It can be installed on-premise in your own data center, in a private or in a public cloud (Google Cloud, AWS, Azure, OpenShift).

You can deploy the toolkit in a Docker container or install a Python library and use the API to integrate it with your databases, catalogs, and enterprise AI tools.

Generate synthetic data from large single- or multiple-table datasets with one-to-many relations, transactional and sequential data.

The Statice SDK supports time-series data, date and time columns, IBANs, names, emails, geographic coordinates, and constant columns as well as the possibility to implement your own custom types.

Save time with our automated data type detection feature. Apply business rules to ensure the synthetic data complies with your data logic. Differential Privacy is built-in so you'll get the highest privacy guarantee in just a few clicks.

To prevent privacy leakages, identifiers can also be automatically detected, simulated, generated randomly, or dropped from the synthesization.

Statice toolkit's privacy mechanisms ensure compliance with the GDPR requirements for anonymization. Synthesization irreversibly breaks one-to-one relationships with the original data. Privacy evaluators enable you to measure reidentification risks.
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Our commitment to achieving the highest standards of data security and integrity has been recognized by the ISO 27001 certification.

⟶ Read our brochure on synthetic data and anonymization

Your synthetic data project in a nutshell

Step 1: Installation and data connections

Step 2: Autonomous learning and training

Step 3: Automatic privacy and utility evaluations

Install the library in your existing infrastructure within minutes. Connect to your data sources and let Statice toolkit automatically detect your data types and enforce your business logic on the synthetic data.

Generate synthetic data with little configuration by utilizing profiles, a ready-to-use set of parameters that enable you to prioritize speed, utility, or privacy based on your requirements.

By comparing statistical properties of synthetic and original data, Statice utility evaluators provide a high-level overview of the utility of your synthetic dataset. Our privacy evaluators assist you in ensuring that synthetic data is protected against reidentification risks.

An enterprise-specific synthetic data ecosystem

Access documentation

Power your workflows and products with synthetic data

Generate synthetic data using our toolkit and overcome your data access challenges.