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Top 1 Data Masking Software SaaS Companies in May 2026

As of May 2026, there are 1 SaaS companies in Data Masking Software. They have combined revenues of $9.7M and employ 87 people. They have raised - and serve - customers combined.

Data Masking Software is designed to protect sensitive information by transforming original data into a format that is not easily identifiable. This is essential for organizations that handle personal, financial, or confidential information and need to comply with various data protection regulations. The software allows for data to be used in testing, analytics, and development environments without exposing the actual sensitive data. Typical features of data masking software include static and dynamic data masking, tokenization, and data obfuscation techniques. Workflows often involve integration with data storage systems, allowing for the automated masking of data sets across various applications and services. Common buyer personas include IT professionals, compliance officers, and data security teams, who prioritize protecting sensitive data while maintaining the utility of that data for analysis and operations.

Companies
1
Revenue
$9.7M
Funding
-
Employees
87

Filters

Sorting: Highest -> Lowest

Filters

Top Data Masking Software Companies

Showing 10 of 1 companies ranked by annual revenue.

1
MageData.Ai

New York, New York, United States

Customer's Choice in Data Masking, Market Leader in Data Security Platforms, Champion in Test Data Management, Strong Performer in Dynamic Data Masking - all titles conferred by Analysts

Revenue
$9.7M
Customers
-
Year founded
2022
Funding
-
Team size
87
Growth
-

Inclusion Criteria

- The product must provide functionality for transforming sensitive data into non-sensitive formats. - It should support multiple data masking techniques, including static and dynamic masking. - The solution must integrate with existing data management and storage systems. - It should enable access control and user authentication to ensure security. - Not just offer data encryption or protection; must also allow for data usability during testing and development.