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Catch+Release is building an AI-powered search engine to help brands license user-generated content

Companies seeking images or videos for their materials materials will typically commission a shoot, or scour stock media catalogs.

Catch+Release is building an AI-powered search engine to help brands license user-generated content

Companies seeking images or videos for their materials materials will typically commission a shoot, or scour media catalogs. Catch+Release, however, wants to help marketers license existing -generated content, and the eight-year-old startup is setting out to build an AI-powered search engine to help brands do just that.

Catch+Release — founded out of San Francisco by Analisa Goodin — has been in existence since 2015: first as an image research firm, and then as a platform for brands to find user-generated content for their various campaigns. The company raised a $14 million in Series A round of funding in 2021, and today it revealed that it has raised an $8 million extension round the same (undisclosed) valuation. Existing backer Accel has returned to the fray, alongside Cervin and Stagwell, with new investors including HarbourVest Partners, Kevin Durant's venture firm 35V, and Gainsight CEO Nick Mehta.

Goodin told TechCrunch that the company decided not to raise a Series B for , due to the current economic environment.

How it works

The Catch+Release platform helps onboard marketers, giving them access to bookmarking tools to find suitable content. Brands can build their collections and galleries by pasting the URLs into Catch+Release, though the platform also offers human curation services for a fee.

Catch+Release lets brands discover content posted by creators from different channels Image Credits: Catch+Release

If a company registers interest in a specific piece of content, Catch+Release examines it through various , for example to see whether there are any logos of other brands, how sensitive the content is, and the number of people in the image or the video. Then it assigns a “licensability” score to that content — something akin to the Zestimate score on Zillow.

Catch+Release then approaches the creator with an offer, and helps them understand the licensing process.

On the other end, Catch+Release proactively asks creators to the platform and plug in their various social channels — such as , Instagram, and YouTube —  so brands can find their content more easily.

The startup charges brands a flat fee for — a term used to formalize licensing from creators. It also charges a marketplace markup on the content after paying creators.

Goodin said that the company has helped creators secure $20 million in licensing fees to date. However, the company is not yet profitable, and is looking to invest its new cash into product and marketing.

“A creator could get paid anywhere between $1,000-$3,000 for working with a big brand,” Goodin said. “However, that payout could be as low as a $100 or $200 for licesing their content to a small brand.”

AI search engine for brands

Looking to the future, Catch+Release is an AI powered search engine for brands, something that Goodin says currently doesn't exist for marketers.

“For example, [let's say] I'm a diaper company and I want to a story that helps my consumers see that we care about our consumers,” Goodin said. “I can't go on Instagram and search something like ‘heartwarming diaper moments.' So we are trying to solve for these kind of use-cases.”

There is a lot of chatter around the use and ethics of generative AI in the creative world. Goodin thinks that while brands require a lot of images and video assets, generative AI tools don't yet offer enough quality — especially in video — to fulfil these needs. She added that Catch+Release customers are not currently thinking about using AI for their campaigns.

Goodin noted that the company has been approached for licensing it data for training generative AI work, adding that Catch+Release would “happily participate” in such program as long as the data is being used fairly and creators are compensated.  However, she didn't specify approached the startup for AI training data.

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Ivan Mehta

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