Mozilla Acquires Privacy Tech Startup Founded By Former Meta Execs

Mozilla, most widely known for its Firefox browser and Mozilla Ads, has acquired Anonym, a company founded in 2022 by former Meta executives Brad Smallwood and Graham Mudd.

Anonym was backed by Griffin Gaming Partners, Norwest Venture Partners, Heracles Capital as well as a number of strategic individual investors.

The acquisition enables Mozilla to further support user privacy while targeting ads.

“This acquisition marks a significant step in addressing the urgent need for privacy-preserving advertising solutions,” Laura Chambers, Mozilla CEO, wrote in a blog post.

Chambers explains by combining Mozilla’s scale and trusted reputation with Anonym’s technology, the company can improve user privacy in advertising as the industry goes through a transformative change.

Growing consumer concerns and increasing scrutiny from regulators have companies focusing on data and privacy practices.



Anonym has what it calls a “Transparency Portal,” the “heart” of its solutions. There it provides partners access to detailed documentation and source code. Partners have a log of all processing performed on their data.

The company explains all operations run on a client’s data that can be reviewed and approved — and processing can be disabled at any time.

The two companies share the same belief. People have a fundamental right to privacy in online interactions. And, digital advertising is critical for the sustainability of free content, services and experiences.

Anonym’s technology combines encrypted data sets from platforms and advertisers. It enables scalable, privacy-safe measurement and optimization of advertiser campaigns, thereby leading a shift toward a more sustainable advertising ecosystem.  

Data sets are matched in a secure environment, ensuring advertisers, publishers, and Anonym don’t access any user level data.

The process results in anonymized insights and models, helping advertisers measure and improve campaign performance while safeguarding consumer privacy.

Privacy algorithms add “noise” to the data, protecting it from being traced back to individual users.

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