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Top 3 Data De-Identification Tools Companies With $5M–$10M Revenue (September 2026)

As of September 2026, Latka tracks 3 data De-Identification tools companies with $5M–$10M in annual revenue. They have combined revenues of $16.3M and employ 133 people. They have raised $1.1M.

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
3
Revenue
$16.3M
Funding
$1.1M
Employees
133

Filters

Sorting: Highest -> Lowest

Filters

Top Data De-Identification Tools Companies With $5M–$10M Revenue

Showing 3 of 3 companies ranked by annual revenue.

1Duality 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
2Datahash 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
3Oblivious 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

Frequently asked questions about Data De-Identification Tools Companies With $5M–$10M Revenue

How many data De-Identification tools companies with $5M–$10M in annual revenue are there?

Latka tracks 3 data De-Identification tools companies with $5M–$10M in annual revenue. Together they generate $16.3M in annual revenue and employ 133 people.

Which data De-Identification tools company with $5M–$10M in annual revenue is the largest?

Duality Technologies is the largest, with $5.6M in annual revenue, founded in 2016.

How much revenue does a typical data De-Identification tools company with $5M–$10M in annual revenue make?

The average data De-Identification tools company in this list makes $5.4M a year, across 3 companies with reported revenue.

Who are the leading Data De-Identification tools vendors with $5M–$10M in annual revenue?

Ranked by annual revenue, the leaders are Duality Technologies, Datahash and Oblivious.

How much funding have data De-Identification tools companies with $5M–$10M in annual revenue raised?

The 3 data De-Identification tools companies with $5M–$10M in annual revenue tracked here have raised $1.1M 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