Finding the right YouTube creator has never been a judgment problem, according to Ramsey Shaffer, co-founder and CEO of Babbl Labs. It’s a logistics problem: hours of scrolling, watching, and cross-checking sponsorship history before a brand can even start a conversation. His company built Scout, a research agent that answers those questions in plain English to close that gap.

Ramsey founded Babbl Labs in Chicago in January 2025 to build what he calls “social intelligence for brands”: tools meant to help brands find the right creators without doing that research by hand. “We’ve essentially built a bunch of agents, a bunch of tools to help brands get their product out there more effectively on social media,” he says.

The company started by running Influencer Marketing campaigns manually for clients, work that surfaced the sourcing and outreach problem Scout was ultimately built to solve. Scout, a self-serve YouTube research agent, launched to the public earlier this month.

Scout is built around a single interaction: a brand types a plain-language question, and the agent returns a ranked list of creators with a fit score attached. Ramsey frames the product’s mascot, a carrier pigeon, as a literal description of the job. “Our whole job is to go out and find the right creators and bring them back to you,” he says.

From Stock Market Signals To Creator Deals

Babbl Labs is Ramsey’s second company. He and a co-founder previously built and exited Uptrends AI, a Minneapolis-based platform that tracked online chatter about public companies to help financial advisors and retail investors spot trends.

That earlier work shaped how Ramsey now thinks about creators. “There’s this whole attention economy that we live in today, where views and what people say online really matter,” he says. “In many cases, views online are worth more than real dollars for a lot of things.”

After the Uptrends exit, Ramsey says the natural next question was not just what people were saying online, but which creators were driving outcomes for brands and how to facilitate those relationships directly. Friends asked him and his co-founder to run creator campaigns for them, and the work snowballed into Babbl Labs.

Manual Deals Taught Babbl What To Automate

Before Scout existed, Babbl operated as a hands-on creator marketing shop, sourcing and negotiating sponsorships for clients directly. Ramsey, who came from a technical background, says the labor involved caught him off guard.

“That was shocking to me,” he says of how much of the work relied on soft skills rather than data, both in producing content that resonates and in identifying creators worth a long-term partnership. “After our first couple of campaigns, I kind of looked at my co-founder. I was like, ‘What did we get ourselves into?’”

The friction was mostly volume: research, outreach, and silence. “It was just so much time scrolling and sending emails, then not getting responses,” Ramsey says. That manual phase became the basis for Scout, built to compress traditionally time-consuming sourcing into a single query.

Scout Scores Creators On Fit, Not Follower Count

Scout assigns every creator a fit score from 0 to 100, built from a set of gates rather than a single metric. A channel needs to be active, post regularly, and clear a minimum average view floor Ramsey puts at roughly 500 views, low enough to include smaller creators but high enough to exclude dormant channels.

The system weighs the topics a channel covers, the audience it reaches, and its recent sponsorship history, then filters out channels it identifies as brand-owned or exclusively sponsored. “What we’re trying to proxy there is not only engagement and the ability to build a compelling catalog of content, but the ability for a brand to sell a product by working with that creator,” Ramsey says.

That framing shapes his critique of how brands typically choose creators. Beyond the familiar habit of over-indexing on subscriber counts, Ramsey points to a subtler mistake: brands asking Scout to surface creators who have already worked with their competitors. “It’s a saturated spot, and it just lacks originality,” he says. “It’s really hard to find the white space when you’re just copying what other people are doing.”

He contrasts this with how typical influencer platforms operate: a brand submits a brief, and roughly 100 creators apply, but most have little relevance to what the brand is actually asking for, since many apply without reading the brief closely. The brand manager still has to sift through every applicant to build a shortlist, a process that can take hours, and even then still has to pursue the creators they want and manage the resulting campaign. Ramsey compares it to a dating app running in reverse: creators pursue brands rather than the other way around. Scout, he says, is built to flip that dynamic, surfacing the creators who best match a brand’s product so the brand can make the first move.

Creators Opt In For Free, Brands Pay By Credit

Scout runs as a two-sided product, though Ramsey says that was not the original plan. Babbl initially built it to serve brands exclusively, then found value in giving creators a profile to shape what brands see about them, including preferred rates and the types of partnerships they want.

“It’s completely free for creators, and we intend to keep it that way,” Ramsey says, arguing that a free, low-friction signup is the fastest way to build the supply side of the marketplace. Where a creator has not opted in, Babbl says its team still reaches out directly to invite them onto the platform when a brand wants to connect.

On the brand side, Scout runs on a usage-based credit model. Brands pay credits per creator they match with, and per creator email address they look up. Current pricing is available on Babbl’s website. Credits are consumed based on how many creators a brand matches with and how many creator email addresses it looks up. Current pricing is available on Babbl’s website.

Distribution Runs Through Claude, Not Just Babbl’s Own Site

Babbl has also built a connector that lets brands query Scout’s data from inside tools like Claude rather than Babbl’s own interface, a choice Ramsey frames as a distribution bet rather than a defensive one. “If our interface can’t get something done, and it’s easier to interact with that data and find creators by having the flexibility of Claude, then we’re perfectly happy with that,” he says.

He also treats usage inside those tools as product research, watching how brands query the data there to inform what Babbl builds into its own dashboard next. The company sees this as a way to move faster than it could by keeping the product fully gated inside its own site.

Alongside Scout, Babbl runs Tripwire, a social listening tool that tracks what creators say about brands and monitors shifts in sentiment. Ramsey says it shares the same underlying technology as Scout and traces back to the monitoring systems.

Ramsey is direct about the limits of what he wants automation to replace. On whether tools like Scout could make human creator-brand matchmakers obsolete, he argues the goal is closer to the opposite: eliminating the scrolling and cold-email work so marketers have more time for relationship-building, not less.

That distinction shapes his closing critique of the industry. Too many brands, he says, still treat creator deals as transactional, closer to buying programmatic ad space than building a partnership. 

“The best possible creator deal is a true partnership, where both sides have a vested interest and a common audience they want to do right by,” he says.

Image source: Babbl Labs

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