RAD Intel is an AI-powered creative intelligence platform that provides data-backed recommendations for influencer and content  marketing campaigns through their proprietary RAD Score™ system.

Founded in 2018 by two serial entrepreneurs, CEO Jeremy Barnett and President Bradley Silver, RAD Intel emerged from their experiences at a Los Angeles-based fashion tech company, where they witnessed firsthand how influencer selection typically relied on intuition rather than data. 

“The influencer recommendation space is a group of really smart people that usually work at an agency, and can paint a pretty picture as to why any given influencer makes sense for a brand,” Jeremy states. “You have a bunch of biases associated with that. There is a real lack of proof points when it comes to artificial intelligence in general. It’s like this black box of information.”

According to Jeremy, this skepticism is justified. The creator economy generates enormous amounts of data, but marketing professionals struggle to trust recommendations from algorithmic systems that offer little explanation for their decision-making process.

This insight prompted a strategic pivot during the COVID-19 pandemic. RAD Intel acquired Atomic Reach, a company with approximately $20 million in investment from backers, including Fidelity Ventures, bringing valuable AI technology and expertise. This acquisition transformed RAD Intel from a conventional influencer platform into an AI-driven creative intelligence solution, designed to provide transparent and trustworthy recommendations to marketing professionals.

The Los Angeles-based company now serves major brands, such as Hasbro, and agencies within the Omnicom Holdings Group that require defensible, transparent AI recommendations for their creator economy investments.

The RAD Score™: Making AI Transparent and Trustworthy

In March, RAD Intel unveiled updates to its proprietary RAD Score™  feature – a system designed to make AI recommendations transparent and trustworthy through what RAD  calls “breadcrumbs of information.”

“We started scoring the influencers based on several different variations of information. Everything from historical performance by industry, to real engagement and traction,” Jeremy explains. “Then we realized, ‘Well, if we can start scoring the influencers, we can also start scoring content.’”

The RAD Score™ creates a ranking system that assigns influencer recommendations a hierarchy of who is most suited for the campaign objective, while ranking content recommendations based on what is likely to perform best. This offers marketers visual, easy-to-understand metrics that justify these choices.

Jeremy illustrates how this works in practice: When a brand like MGM wants to reach a specific audience, RAD Intel’s algorithm gets to work, surfacing the topics that the potential audience cares about now. From there, the RAD Score™ ranks influencers based on past performance with that segment and how well their content aligns with current interests.

The result? Influencer partnerships that are not based on follower counts. Not based on guesswork. Just data-backed decisions that drive ROI.

The enhanced RAD Score™ includes four key components:

1. Advanced Predictive Analysis: The system forecasts performance potential compared to industry benchmarks. As Jeremy explains, “If you utilize this audience for this objective and you utilize this influencer to push out a series of messaging that connects to the things that the audience cares about most, then the idea is you are going to perform anywhere from 1.5x to 7x better than industry benchmarks.”
   
2. Real-Time Content Optimization: Beyond initial recommendations, RAD Score™  provides ongoing suggestions to optimize content for maximum impact. “Maybe it needs to be cut down from 30 seconds to 24 seconds. Maybe the captions need to be different,” Jeremy notes. “There are best practices for the audience and influencer on each product and platform.”
   
3. Cultural Relevance Assessment: The system evaluates potential content against current cultural conversations, helping brands avoid tone-deaf marketing disasters. “Cultural relevancy as it relates to the brand can be a doomsday event if you’re a marketer, if you don’t do it right,” warns Jeremy, referencing the Bud Light controversy that resulted in “several billion dollars in market cap damage.”
   
4. Brand Safety Verification: Before recommending influencers, the platform conducts thorough safety checks for the brand as well. “We look at trademark violations, copyright issues, and competitive brands that they potentially promoted. We look at provocative content and controversial content,” Jeremy details.

A Three-Pillar Approach to Creative Intelligence

RAD Intel doesn’t start with influencer selection; it starts with audience understanding. “We tell our customers what their potential buyers and current audiences care about right now – based on real-world interests, trending topics, and cultural preferences,” says Jeremy. “And that serves as a basis and baseline for who you should book and why.”

By anchoring influencer strategy in what the audience actually cares about, RAD Intel ensures brands aren’t just choosing influencers—they’re choosing outcomes. 

RAD Intel’s system operates on three interconnected pillars that form their core value proposition:

1. Audience Identification: The platform first identifies exactly who the brand should target and why. “Our artificial intelligence looks at the historical content performance patterns across a wide set of different influencer connections that we have,” explains Jeremy. This includes platforms like “TikTok Creator Marketplace and Reddit” as well as “different Google and Bing properties.”
   
2. Influencer Selection: Based on audience insights, the system recommends creators most likely to mobilize that specific audience to take action. As Jeremy notes, “The idea is understanding the different historical performance patterns associated with influencer profiles that match the audiences and the nuanced interests associated with those audiences.”
   
3. Content Strategy: The platform then determines what type of content these creators should produce. “So those are the three pillars of content creation. And we’ve created an end-to-end platform that delivers on those three pillars for our customer base,” Jeremy summarizes.

What distinguishes this approach is that RAD Intel doesn’t take creative control away from marketers. As Jeremy emphasizes, “We leave the strategy in the hands of the person in charge of the strategy, but we’re helping that person deliver a better strategy for the campaign objective. It’s still their decision.”

Real-World Impact and Market Response

RAD Intel’s solution to the AI trust gap has gained traction with major brands and agencies. The company works directly with enterprise brands like MGM, where, as Jeremy explains, “We represent some of the biggest household names today. We run everything from content marketing to influencer activations to brand safety and crisis management.”

It also partners with major agency networks: “We service agencies within the Omnicom Holdings Group umbrella, and they actually have hands-on keyboards.” According to Jeremy, they’ve published case studies with brands including “SweetGreen, MGM, Skechers, The Black Tux, and many household brands in high demand today.”

And RAD’s approach to providing transparent, trustworthy AI recommendations has driven notable business growth in the last year alone. “We’ve already doubled last year’s sales in the first quarter of this year, and we’re projecting a 4x-5x multiple over last year,” he says.

Building on this momentum, RAD Intel has launched a growth initiative. “We’ve recently launched a strategy called AIBO (Artificial Intelligence Buyouts),” Jeremy explains. “We’re looking to buy companies that do anywhere from $5 million to $50 million a year in revenue, specifically operating in the creator economy, and are EBITDA positive.”

Expanding Creative Intelligence

While developed specifically for influencer marketing, RAD Intel’s approach to transparent AI recommendations has revealed unexpected applications across broader marketing disciplines.

“We’re seeing with our agency partners that the creative intelligence isn’t just for the creator economy, but it can be used for product launches, it could be used for creative strategy across the board for a media campaign, it could be used to think through the elements associated with what you’re going to do with digital content in any context,” Jeremy reveals.

He continues, “It just works incredibly well. It’s been produced for the influencer and creator economy, but we’re seeing it being used in several other places, which we’re excited about.”

Trusted AI in the Creator Economy

Jeremy sees addressing the trust gap in AI as increasingly important in the creator economy, particularly as AI-generated content becomes more advanced.

“It’s differentiation. I think also embracing the age of artificial intelligence and where AI is going,” Jeremy says about what winners in the creator economy are doing. “As artificial intelligence continues to change, how the content looks will improve. It’s just going to get better and better.”

And he expects major shifts in how creators and brands interact with AI. “One year from now,” Jeremy predicts, “influencers will license their likeness to a brand, approve the messaging, and let the brand generate content on their behalf. The result? Fully AI-generated media that looks and feels real—without the influencer ever stepping in front of a camera.”

Jeremy believes that in such a fast-moving space, transparent and explainable AI is becoming essential—not just to build confidence among marketers, but also to maintain trust with creators.

“Understanding how AI is shaping audience insights, content creation, and influencer partnerships will be key to leading effectively,” he concludes. “It’s not just about predicting the future—it’s about knowing what tools are available right now to create the most effective, resonant campaigns possible.”