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Top 15 Data De-Identification Tools Companies (September 2026)

As of September 2026, Latka tracks 15 data De-Identification tools companies. They have combined revenues of $147.3M and employ 1.1K people. They have raised $107.1M.

Every company below sells data De-Identification tools 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.

What Data De-Identification Tools Companies do

Data De-Identification Tools are specialized software solutions designed to remove or obscure personally identifiable information (PII) from datasets, enabling organizations to protect individual privacy while making data available for analysis and research. These tools are essential in various sectors, including healthcare, finance, and education, where sensitive information needs to be handled in compliance with privacy regulations such as HIPAA and GDPR. The primary use cases for Data De-Identification Tools include preparing data for research, analytics, and machine learning while ensuring that the data cannot be traced back to any individual. Typical features of these tools include data masking, tokenization, pseudonymization, and the application of data minimization principles. Common buyer personas include data privacy officers, compliance managers, and IT security professionals who are responsible for safeguarding sensitive data assets within their organizations. Organizations that utilize these tools benefit from improved data security, enhanced compliance with legal requirements, and the ability to share data in an anonymized form that still retains its utility for analysis and decision-making. The adoption of Data De-Identification Tools is becoming increasingly critical as data breaches and privacy concerns continue to rise in today’s digital landscape.

Companies
15
Revenue
$147.3M
Funding
$107.1M
Employees
1.1K

Filters

Sorting: Highest -> Lowest

Filters

Top Data De-Identification Tools Companies by revenue

Showing 10 of 15 companies ranked by annual revenue.

1Protegrity Usa, Inc. logo
Protegrity Usa, Inc.

Stamford, Connecticut, United States

Unleash the Power of Secure Data We safeguard privacy, ensure data is protected everywhere, and fuel innovation with secure AI.

Revenue
$50.7M
Year founded
1996
Funding
$6M
Team size
378
2Very Good Security logo
Very Good Security

San Francisco, California, United States

Very Good Security is a fintech & data security enablement platform helping to maximize the value of data without compliance & breach risk.

Revenue
$33.2M
Year founded
2015
Funding
$60M
Team size
270
3Spirion logo
Spirion

Tampa, Florida, United States

Developer of enterprise data management software intended to help businesses reduce their sensitive data footprint. The company's software focuses on discovering, classifying, monitoring and protecting personal information, medical records, credit card numbers, and intellectual property stored across the enterprise, within the e-mail, and in the cloud, and specializes in the high-precision search and automated classification of unstructured data, enabling clients in the healthcare, public sector, retail, education, financial services, energy, industrial, and entertainment markets to proactively minimize the risks, costs and reputational damage of successful cyber attacks

Revenue
$27.3M
Year founded
2006
Funding
$20M
Team size
72
4Duality Technologies logo
Duality Technologies

Hoboken, New Jersey, United States

Duality's breakthrough innovative technologies eliminate the conflict between data protection and business growth and innovation. The Duality Data Analytics and AI platform is built upon advanced encryption methods, hardware technologies, and machine learning techniques that protect sensitive data while in use. Duality is the only multi-PET platform with the ability to combine various technologies to meet the unique needs of sensitive data operations. These guardrails streamline and enhance the data operations critical for data-driven insights and innovations by eliminating bulky, expensive, and limiting processes like data anonymization and tokenization. Traditional data protection methods prevent organizations from truly adopting and leveraging advanced models to their benefit, resulting in restrictive policies like "no sensitive data can be used for model training." With Duality, organizations can confidently customize 3rd party models on their own data without fear of data leaks. Model providers can scale model customization knowing that their proprietary model is never exposed to the customer, preventing competitive intelligence leaks. Financial institutions can turn their manual KYC requests into self-service operations, greatly enhancing the speed and success of these expensive requirements. The benefits of data protection guardrails span from efficiency gains, to unlocking previously inaccessible data, to slashing costs on high-security infrastructure.

Revenue
$5.6M
Year founded
2016
Team size
51
5Datahash logo
Datahash

Dubai, Dubai, United Arab Emirates

Datahash is a bootstrapped, profitable SaaS company headquartered in Dubai, specializing in privacy-safe first-party data infrastructure.

Revenue
$5.5M
Year founded
2019
Team size
50
6Oblivious logo
Oblivious

Dublin, Ireland

Oblivious builds tools to allow you to use your sensitive data with internal and external partners while keeping it private and secure

Revenue
$5.2M
Year founded
2020
Funding
$1.1M
Team size
32
7Data Safeguard Inc. logo
Data Safeguard Inc.

Santa Clara, California, United States

An Artificially Intelligent, humanly impossible, previously unsolvable, hyper-accurate approach to comply with data privacy compliance and prevent synthetic fraud losses.

Revenue
$4.7M
Year founded
2021
Team size
43
8CaseGuard logo
CaseGuard

Arlington, Virginia, United States

CaseGuard is an AI Redaction Solution. Everything you need to redact and enhance any video, audio, image, or document in one redaction solution. Very flexible, affordable, easy to use, secure, fast, multilingual, and ready to integrate with other systems. CaseGuard helps law enforcement agencies, federal agencies, hospitals, schools, shopping centers, airports and private companies manage all their media redaction needs in one easy to use redaction software.

Revenue
$4.1M
Team size
37
9brighter AI logo
brighter AI

Berlin, Berlin, Germany

Generative AI for Privacy | Named "Europe's Hottest AI Startup"

Revenue
$3.1M
Year founded
2017
Team size
28
10Sarus logo
Sarus

Paris, France

Use personal data for analytics and ML, safely and seamlessly

Revenue
$2.7M
Year founded
2020
Team size
18

Frequently asked questions about Data De-Identification Tools Companies

How many data De-Identification tools companies are there?

Latka tracks 15 data De-Identification tools companies with reported revenue. Together they generate $147.3M in annual revenue and employ 1.1K people.

Which data De-Identification tools company is the largest?

Protegrity Usa, Inc. is the largest, with $50.7M in annual revenue, founded in 1996.

How much revenue does a typical data De-Identification tools company make?

The average data De-Identification tools company in this list makes $9.8M a year, across 15 companies with reported revenue.

Who are the leading Data De-Identification tools vendors?

Ranked by annual revenue, the leaders are Protegrity Usa, Inc., Very Good Security, Spirion, Duality Technologies and Datahash.

How much funding have data De-Identification tools companies raised?

The 15 data De-Identification tools companies tracked here have raised $107.1M in disclosed funding between them.

Related Data Privacy Software categories

Inclusion Criteria

- Must remove or obscure identifiable information to protect individual privacy - Should comply with industry regulations (e.g., HIPAA, GDPR) governing data privacy - Must provide options for data masking, tokenization, or pseudonymization techniques - Should enable organizations to analyze and utilize data without revealing personal identifiers - Not just focused on data storage; must also ensure compliance throughout data processing workflows - Should support multiple data formats and sources to serve diverse organizational needs - Designed for use by data privacy officers and compliance managers in their efforts to safeguard sensitive information