Statice
Statice
Faster data access, better privacy
Make data privacy a competitive advantage. Use synthetic data to unlock and accelerate your data operations.
Generate real value from synthetic data
Data governance silos and regulatory constraints affect your ability to use data? Our solution anonymizes and removes data from the scope of regulations such as the GDPR, reducing time it takes you to access from months to hours.
X4 Faster time-to-data on average
97% Effectiveness in ML performance observed
0€ Total of GDPR fines on synthetic data
Unlock insights
PRODUCTS
1. Synthetic data software for faster data operations
An enterprise-level synthetic data tool that eliminates access barriers to data processing in a matter of minutes.
Synthetic data generation
Make your data accessible for insights
Having trouble gaining access to sensitive enterprise data? Use Statice software to generate anonymized synthetic data and make it available within hours without affecting compliance.
Fully synthetic data
Create new, entirely artificial datasets using your original data.
Multiple table support
Synthesize relational datasets with multiple tables and time-series data types.
Unique deep learning approach
Benefit from state-of-the-art deep learning models that adapt to your data and use cases.
2. Power your workflows and products with synthetic data
Generate synthetic data using our toolkit and overcome your data access challenges.
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.”
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.”
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.”
3. Data anonymization expertise at your service
Pros
- Working on a hard problem, for global enterprises, with a strong team.
- Flexible working environment / times / locations.
- Transparent culture and direct access to management.
- Solutions helping businesses protect data privacy and their users
- Many ways to bring impact and grow as an engineer or manager
- Remote-first, good work-life balance
- Multicultural and diverse team
Cons
- Emerging market means that feedback is slow and lots of customer education is necessary.
- Company retreats are complicated for non-EU citizens due to COVID restrictions and closed borders
- It can take some time to keep up with the pace of work and get used to the data science language