As of August 2026, Latka tracks 1 data masking software companies. They have combined revenues of $9.7M and employ 87 people.
Every company below sells data masking software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
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.
Sorting: Highest -> Lowest
Showing 1 of 1 companies ranked by annual revenue.
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
Latka tracks 1 data masking software companies with reported revenue. Together they generate $9.7M in annual revenue and employ 87 people.
MageData.Ai is the largest, with $9.7M in annual revenue, founded in 2022.
The average data masking software company in this list makes $9.7M a year, across 1 companies with reported revenue.
Ranked by annual revenue, the leaders are MageData.Ai.
- 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.
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