31 July 2025

Rwazi co-founders Joseph Rutakangwa (left) and Eric Sewankambo (right), following the company’s $12M Series A to accelerate its AI copilot.

 

When Joseph Rutakangwa landed his first consulting gig in 2013, advising a global consumer goods firm, he encountered a familiar problem that would eventually spark his entrepreneurial journey: a critical lack of reliable data in emerging markets. He recalls vividly the high-stakes decisions around market entry—where to invest, which consumers to target, at what price, through which channel—and how there was no dependable information to guide those choices outside of Western markets.

“Back in 2013, I landed my first consulting job with a global multinational... It all came down to one thing: data. And that’s where everything broke down.” Whether government statistics, trade agency reports or high-cost consultancy panels, the data was invariably outdated, fragmented, or unreliably small in scale. Even second- or third‑party datasets failed to capture what Rutakangwa calls “what was considered, compared, or rejected”—only showing what had actually sold. The result? Decisions grounded in gut instinct costing millions in wasted marketing and lost sales.

That frustration ignited the question: Is this just a one-off pain point, or a systemic issue? Over eight years, consulting across sectors—from consumer goods to transport and energy—Rutakangwa and his cofounder Eric Sewankambo saw the same data gaps. Eventually, Rutakangwa pivoted from consulting to building tools that collected raw inputs, but still realized these were either second‑party or third‑party data, lacking the clarity born of voluntary, first-hand input.

The Birth of Zero‑Party Data and Rwazi

“I began to wonder: is this just a problem in one sector? Or one company?” Rutakangwa reflected. The answer came in the realization that the most authentic data comes directly from consumers: voluntarily shared, real-time, rooted in daily routines rather than panels or models. With Eric’s background in building robust data pipelines, they spent almost three years refining their core methodology before founding Rwazi in 2021.

What they ultimately built was a system that captures “zero‑party data”—consumption patterns, pricing, locations, motivations—straight from consumers via mobile and web-based agents (sometimes called “mappers”). This approach allows enterprises deep, timely visibility across markets that had previously been opaque.

Despite facing investor scepticism initially—every pitch getting shut down with feedback that they weren’t the right team—the Rwazi founders pivoted. They went directly to prospective customers, asking: “What’s the smallest thing you’d pay for today?” Their answer: “Show us what’s happening in the market right now, directly from consumers—and we’re in.” That empirical feedback became their north star, attracting clients rapidly and achieving profitability within months. “Companies tried to acquire us before we even announced ourselves to the market,” Rutakangwa says—though they remained committed to building for the long haul.

What Rwazi Has Built: A Global Decision‑Intelligence System

With initial momentum and revenue proving product-market fit, Rwazi secured funding and scaled. Today, the company provides live, global, high-fidelity decision intelligence—tracking billions of consumer signals across 190+ countries and operating in real time.

The system broke ground through three successive levels:

• Level 1: Capture—building infrastructure to collect zero‑party data at scale.
• Level 2: Interpret—processing disparate inputs (images, text, voice, video) through custom-built pipelines to turn raw signals into actionable insight.
• Level 3: Recommend—launching Lumora, a contextual AI engine that identifies growth gaps, tests strategic moves, and offers tactical recommendations tailored to each brand’s unique context.

This architecture powered their shift from profitable startup to enterprise platform—enabling clients to extract 10X or 100X value over legacy research methods.

Sena: The New AI Copilot

But Rwazi didn’t stop there. Teams asked, “How do we execute?”, and the response was Sena, the company's AI copilot. Sena transforms raw data and insights into operational clarity. Rutakangwa describes it as compressing the entire path from insight to execution: plain-language queries elicit context-aware recommendations tailored from zero‑party data, with step‑by‑step guidance toward execution.

With Sena, decision-makers don’t navigate dashboards or write SQL—they ask a question and get not just an answer, but a plan: gaps to fill, pricing scenarios to test, campaign adjustments to simulate. Sena is positioned to integrate with enterprise reporting, workflow, and communication tools—to become “connective tissue between intelligence and action. It’s not just an analytics layer—but a partner embedded in daily operations.

Simulation and Strategy: What’s Possible Today

Rwazi today offers simulation-based decision-making: identify which consumer segments matter most, detect drivers of churn or defection, evaluate message or price shifts before investment. These simulations provide insight on projections around revenue, market share, and loyalty—without spending a dollar.

Looking to the future, Rutakangwa envisions a system that not only recommends but executes—an AI layer that sees patterns humans miss, simulates every possible action, and recommends or even carries out the optimal one. That’s the ultimate pivot—from manual, fragmented decision-making to continuous, intelligent orchestration.

Who Uses Rwazi and Why It Works

Rwazi primarily serves consumer-facing companies—Fortune 500 brands across sectors like FMCG, payment services, telecom, and consumer goods. Global sales and marketing units use Sena to simulate decisions around pricing, messaging, channel allocation, and budgets—often in high-velocity environments where small behaviour shifts yield outsized effects.

“What made the difference wasn’t just access to data—it was having a system that could evaluate the move in real time and simulate a better one,” Rutakangwa recounts of a client story: a major brand planned to double down on a campaign based on precedent—but Sena flagged signs of fatigue among target segments and proposed a revised strategy. That recommendation outperformed expectations significantly.

Fuelling Growth: Series A and Future Priorities

In July 2025, Rwazi closed a $12 million Series A round led by Bonfire Ventures, plus Santa Barbara Ventures, Newfund, and Alumni Ventures.

“That raise lets us put a real-time AI copilot in the hands of every decision‑maker — so teams can move faster, smarter, and with total clarity,” Rutakangwa said. The new funds will deepen simulation capabilities, expand global data infrastructure, and enhance Sena’s contextual recommendation engine across business functions.

The financing follows the $4 million seed round from early 2023, also led by Bonfire Ventures, which helped Rwazi scale initially into Africa and south Asian markets across fast-moving verticals.

Looking ahead, funding is not about experimentation—it’s about scale. Rwazi plans to double down on R&D, especially around Sena; expand teams in enterprise sales and customer success; and continue pushing global expansion. “Our platform can now be used by any business anywhere in the world... The goal is to turn Rwazi into the decision infrastructure layer for every team that needs to move fast and act smart.”

Beyond Insight: Toward Generative, Agentic AI

With generative AI transforming workflows and decision-making, Rwazi is positioning itself to lead the next wave. Sena is evolving from tool to operator: able not only to surface recommendations, but to execute when linked with enterprise systems. “In this next era, speed and precision will define competitive advantage... We’re building the operator every enterprise team needs.”

Rutakangwa’s deep first-hand frustration with unreliable data sources, layered with a conviction in consumer truth and real-time intelligence, has turned into a platform trusted by global brands. As legacy research firms like GfK and Ipsos struggle with static models, Rwazi’s zero-party, real-time infrastructure offers a fundamentally different path—one where intuition is replaced with simulation, and insight becomes action.

Why It Matters

In fast-moving global markets—where emerging economies like India, Brazil, Turkey, and sub‑Saharan Africa are shifting rapidly—companies can no longer afford lagging research, assumptions, or gut calls. The ability to anticipate shifts, test scenarios, and execute confidently is now central to growth and retention.

Rwazi’s rise is driven by identifying a critical gap and refusing to settle. Its innovation lies not just in collecting better data, but in building an end-to-end system—from consumer signal to strategic action.

As brands increasingly demand immediacy, clarity, and high fidelity, Rwazi’s "AI copilot" offers a compelling alternative to legacy market research: one that promises not just foresight, but the power to act.