Keeping track of sensitive data in databases can be difficult.

This tool uses machine learning in order to intelligently discover sensitive data in any and all columns in a SQL Server database. It uses a combination of scanning actual column values along with the names of SQL Objects to determine if a column contains sensitive data.

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How it works

Using machine learning allows the tool to intelligently discover sensitive data without the need for users to spend time on confusing configuration. The tool would already be trained to identify sensitive data, inspired by the data requirements of current regulations such as ISO 27001, PCI-DSS and HIPAA.

If you have sensitive data that isn't already covered by the available options (for example, custom identifiers), then the tool will offer custom configuration through the use of, for example, regular expressions. The regular expressions are used as part of the scan to identify sensitive data appropriate to your specific environment.

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Data masking

We’re investing heavily into building a data masking tool to help you leverage your production data and make your testing more effective, whilst ensuring your data is safe and secure.

Do you want to get in on the ground floor and help us shape the product for your use case? We'd love to work with you and gain deep insight from your industry experience.

Regulation & policy compliance

Not only do we understand how important the security of your data is, we also recognise how important it is to be confident that you’re not contravening regulations.

We think it should be easier to find all the sensitive data in your database without having to go through every table and column by hand.

Data generation

For those who aren't able to access production data, let alone mask it, we're working on novel technologies for better data generation.

Imagine generating data that is 100% safe and realistic; we're developing machine learning techniques to create realistic data that matches the profile of your production data, without putting production data at risk.

Code analysis

We've heard that production data is used in testing and QA environments in order to validate code written in development. Which got us thinking; what if you could analyse your code at development time, assessing it for its ability to cope with real-world data scenarios.