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Noise Raises $5.5 Million to Expand the Paid Creator Market

Noise has closed a $5.5 million seed funding round, bringing its total funding to $7.2 million, and is betting on turning ordinary smartphone users into brand-employed content creators who are paid based on the number of views.

2026-09-16
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Noise Raises $5.5 Million to Expand the Paid Creator Market

Marketing platform Noise announced that it raised $5.5 million in a seed funding round led by Capital Midwest, M25, and Grishin Robotics, with participation from Capitalize VC and investors from companies including DoorDash. This brings the company’s total funding to $7.2 million.

Noise connects brands with ordinary people who want to produce content for platforms such as TikTok, Instagram, Facebook, and YouTube, without requiring them to have a large number of followers. The brand publishes the campaign brief and budget on the platform, while Noise selects participants and helps manage content, relationships, and payments. Creators are paid based on the number of views, rather than receiving a fixed fee for each campaign.

A Different Model from Influencer Marketing

The platform targets an operational problem facing brands, particularly companies with limited budgets: reaching a large number of creators and managing work with them individually can be costly and slow. Noise says its largest brands run campaigns with several thousand creators in an automated manner, while many of its current clients come from mobile applications and startups seeking influencer-based marketing.

The company says it currently has 1.5 million creators on the platform. According to CEO Diego Kafie, the top creators earn more than $100,000 annually, with Noise receiving fees from the amounts brands pay after the views are delivered. These figures come from Kafie, and the article provides no independent details about users’ average earnings or the method used to calculate paid views.

From the Playbite Experiment to an Independent Platform

Diego Kafie, Stu Feldt, and Nic Weber founded the company in 2025, after spending two years developing the mobile gaming app Playbite. During that experience, the team tested recruiting ordinary players and teaching them to produce social content to promote the app. The number started at five people, then grew to 10, 25, and 100, according to Kafie, and the team observed an increase in app installs as those participants published content daily.

That experiment formed the basis of Noise’s idea: instead of relying on well-known, highly paid influencers, new users can be trained to produce marketing content and campaigns can be distributed among a large number of them. The company believes this model lowers the cost of reaching audiences while giving users an opportunity to earn their first income online.

What Changes in Practice?

Noise has also launched a program called Organic-to-Ads, which allows brands to use videos produced by creators in paid advertisements on Meta and TikTok, in addition to distributing them through the creators’ accounts. As a result, the video’s role is not limited to organic reach from a user’s post; the brand can also allocate an advertising budget to expand its reach.

The company says new participants undergo training modules on producing content for brands and initially receive only specific campaigns. As they complete more training and obtain additional work, higher-paying opportunities may become available to them. Kafie also confirms that brands set payment rates and that creators are free to accept or reject an offer.

Noise plans to use the new capital to develop product capabilities and hire more employees. The round’s significance lies not merely in adding another marketing tool, but in attempting to turn commercial content production into a broad market based on training and automated distribution rather than celebrity and follower counts. However, questions about users’ actual earnings, the criteria for calculating views, and the terms for using content in paid advertisements still require further clarification before the model can be evaluated beyond the company’s claims.

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