Here is a hypothetical scenario – a creator with fewer followers in a small Kenyan town can deliver higher campaign ROI than someone with larger follower counts in major cities; yet every major creator marketplace’s AI will recommend the account with more followers. 

This systematic misreading of influence patterns across African markets represents a core flaw in how global AI systems approach creator marketing—one that costs brands significant funds in misdirected spending and leaves high-performing creators invisible to opportunity.

Cedric Nzomo recognized this technical blind spot after 12 years of running creator campaigns across eight African markets through his agency, Verge Group. “Local context is not well understood by global GPTs,” says Cedric, who recently co-founded Zaumu, Kenya’s first AI-driven creator marketplace. “The gap we want to close is specifically around understanding not just content creators but the ecosystem around them to interpret what influence is properly.”

The scale of this AI misalignment becomes clear when examining Kenya’s advertising. While 2,500 billboards generate over $50 million annually, the country’s entire influencer market captures just $2.5 to $3 million, according to Statista, though Cedric estimates the true figure to be closer to $5 million. Despite shifting consumer behavior patterns, this disparity favors traditional advertising over creator marketing.

Zaumu serves brands and agencies seeking creator partnerships across Africa, where traditional engagement metrics fail to predict business outcomes. The platform aims to help out companies frustrated by global creator marketplaces that optimize for follower counts and universal engagement rates rather than understanding how influence propagates through different social networks, economic conditions, and cultural frameworks across African markets.

Proprietary AI Architecture Built from African Data

Cedric’s technical solution centers on three interconnected AI engines designed specifically for African creator ecosystems. Each engine is trained on local performance data rather than adapted from global models. 

The analytical AI engine processes campaign performance data to understand ROI drivers across different creators, content types, platforms, and time periods. 

“The analytical one is basically just going to try to understand what actually drives ROI and who actually drives ROI and what type of content is working in what period of time, on what channels, with what types of creators,” Cedric explains. This engine learns from completed campaigns with measurable business outcomes rather than theoretical engagement metrics.

Building on these insights, the comparative AI benchmarks creators against relevant local peers rather than global standards. Instead of comparing all lifestyle creators universally, the system focuses on meaningful regional comparisons between creators with similar follower ranges operating in comparable markets.

The predictive AI monitors trends and creator growth patterns to identify emerging opportunities before they become obvious to global platforms. “The predictive is basically going to monitor over time how things are moving and try to be able to highlight when trends are about to pick up, creators are about to grow, and all these different types of things,” Cedric notes, adding that this forward-looking capability helps brands identify high-potential creators before their rates increase or availability decreases.

The value proposition lies not in the individual engines but in their integration with locally specific training datasets. “We’ve very intentionally built those things underneath the platform so they can train and learn using local context,” Cedric explains. “So that when we eventually get to the point where we’re launching this feature that helps you trend map, we actually have 10,000 cases to be able to say we’ve trained this on 10,000 jobs.”

Why Local AI Training Creates Competitive Advantages

As Cedric explains, Zaumu’s data-first approach addresses core limitations in how global AI systems approach creator marketing optimization. While most platforms train on engagement metrics that may not correlate with business outcomes, Zaumu’s AI learns from campaigns with measurable ROI across different African markets. The result is an algorithmic understanding of what actually drives performance rather than what theoretically should work based on global patterns.

While competitors might eventually copy platform features, replicating years of local training data becomes exponentially more difficult. Each completed campaign strengthens the AI’s understanding of local influence patterns, creating compound advantages that improve over time. 

“We want to be able to analyze these things and give you concrete data to say, well, on TikTok it matters, on Instagram it doesn’t, and advise people on how to be able to build those communities,” Cedric explains.

Building this AI infrastructure required bootstrapping development using revenue from Verge Group rather than pursuing venture capital, a constraint that forced creative technical decisions. 

“We don’t have the same VC infrastructure as in the U.S. and the West in general,” Cedric acknowledges. However, this limitation required building sustainable, revenue-generating AI rather than pursuing theoretical capabilities that might not translate to business value.

Business Impact Through Localized Intelligence

Zaumu’s AI systems generate business metrics that creator economy professionals can evaluate directly. The platform provides brands with automated side-by-side campaign performance comparisons, trend analysis, and creator scoring systems that reflect local market realities rather than universal standards. 

“If, let’s say, you have 10 creators working on this campaign, you’ll be able to see the metrics side by side, the posts side by side, you can see what’s the best,” Cedric explains.

The Zaumu score system demonstrates how locally trained AI provides more nuanced creator evaluation than global metrics. Rather than universally penalizing follower fluctuations, the system considers local performance patterns and the quality of engagement. 

“Even though I lost 500,000 followers, my engagement rate went up by 40%. So, it’s a positive thing,” Cedric illustrates, adding that global AI might flag follower loss as negative, while local AI understands this could indicate improved audience quality and higher engagement rates.

This localized intelligence extends to platform-specific insights that help brands optimize their campaign strategies based on regional user behavior, rather than relying on global platform trends. The AI analyzes how content performs differently across platforms within specific markets, providing actionable insights for campaign planning and creator selection.

Platform workflows integrate this AI into campaign management processes. When brands list opportunities, the matchmaking AI sorts incoming creator proposals based on locally trained performance predictions rather than surface-level metrics.

Technical Infrastructure for Continental Expansion

Zaumu’s AI architecture is designed to scale across Africa’s diverse markets while maintaining local intelligence quality, with plans to operate in 10 African markets within five years. 

According to Cedric, each new market requires additional training data to understand local context, but the underlying technical framework remains consistent. “We really want to get across the continent in less than 10 years. And it’s a tall feat because it’s over 50 different countries with 50 different economies,” he notes.

He reveals that this scaling approach involves training AI systems that recognize both pan-African patterns and market-specific nuances. The technical challenge requires understanding how influence operates differently across various economic conditions, cultural contexts, and platform usage patterns while identifying broader trends that apply across multiple markets.

Building AI systems for African markets also requires addressing infrastructure challenges that are not present in developed economies. Zaumu integrates with local payment systems, supports multiple currencies, and operates efficiently on varying internet connectivity levels. 

“We’re building our own payment gateway because we realize there’s a real bottleneck in terms of finding a platform that can work across the continent,” Cedric explains.

Implications for Global Creator Economy AI

Cedric points out that Zaumu’s locally trained approach raises important questions about AI development in creator economy platforms worldwide. If local context significantly impacts campaign performance, then global platforms using universal AI models may systematically underperform in non-Western markets. 

He believes the principles behind training AI on regional creator data can be applied to other emerging markets where global platforms struggle to understand local influence dynamics.

The emphasis on transparency also distinguishes Zaumu’s AI from black-box algorithms that provide recommendations without explanation. Instead, the system highlights why certain creators or strategies are recommended, enabling brands to understand local market dynamics rather than blindly following algorithmic suggestions.

Cedric’s vision extends beyond technical innovation to encompass cultural impact and global perspective sharing. “We prefer to be ambitious. We prefer to have the big dream and chase it down,” he concludes.