From Stanford to São Paulo: Building Behavioral Infrastructure for the World

How a Stanford robotics researcher and AB InBev innovation lead found her mission in behavioral intelligence, and why Brazil is the perfect starting point.

Published 2026-04-24 · 5 min read

From Stanford to São Paulo: Building Behavioral Infrastructure for the World

The Spark at Stanford

When Luciana Frazao joined Stanford's Autonomous Robotics and Manipulation (ARM) Lab, she expected to build robots. What she discovered instead was a deeper question: why do machines struggle so much to understand human intent? Robots could detect objects, calculate trajectories, and execute precision movements. But they could not anticipate what a person needed next. The missing piece was never compute power or sensor quality. It was behavioral understanding.

That insight stuck with Luciana through her entire career and eventually became the foundation for Fluence.

Scaling Innovation Across 50 Countries

After Stanford, Luciana joined AB InBev as a Global Innovation Lead. She worked across more than 50 countries, deploying technology solutions at a scale few people ever experience. The role taught her two critical lessons.

First, infrastructure beats applications every time. The projects that transformed AB InBev's operations were not flashy apps. They were foundational layers that every team could build on top of. A shared data pipeline mattered more than a hundred dashboards.

Second, personalization at global scale requires understanding people, not just demographics. AB InBev served billions of consumers across wildly different cultures. Generic segmentation failed repeatedly. The teams that succeeded were the ones who understood local behavioral patterns, the rhythms of how people actually interacted with products.

Why Behavioral Intelligence

Every AI system Luciana evaluated during her career hit the same wall. Models had incredible capabilities but zero understanding of the humans they served. A chatbot could generate perfect financial advice but had no idea the user was anxious about money. A recommendation engine could rank thousands of products but could not tell that a shopper always abandoned cart when prices crossed a certain threshold.

The problem was clear: AI applications lacked a behavioral understanding layer. Not another analytics dashboard. Not another CRM field. A real-time, continuously updated intelligence layer that captured how people behave and made that understanding available to every AI system through a simple API call.

Fluence became the answer. One API endpoint, \GET /context/{user_id}\, delivers model-ready behavioral context that transforms any AI interaction from generic to genuinely personalized.

Why Brazil First

Choosing Brazil as the beachhead market was deliberate. Brazil has one of the most advanced fintech ecosystems in the world. Over 80% of the adult population uses digital banking. PIX, the instant payment system, processes billions of transactions monthly. Companies like Nubank, Stone, and PicPay have built massive digital platforms that serve tens of millions of users.

These platforms generate enormous volumes of behavioral signals. But most of them feed those signals into basic analytics tools that track what happened without understanding why. The opportunity to add a behavioral intelligence layer is massive and immediate.

Brazil also has strong data protection regulation through LGPD, which aligns perfectly with Fluence's privacy-first design. Fluence analyzes behavioral patterns only and never touches content. Compliance is built into the architecture, not bolted on as an afterthought.

The Proof

Before launch, Fluence ran a pilot with Fortics, processing 3.4 million behavioral profiles. The results validated the entire thesis: 40% churn reduction, 2.3x conversion lift, and 3.5x improvement in ML model accuracy. Integration took less than 10 hours. These numbers gave Luciana the confidence to go all in.

The Accelerator Advantage

Fluence earned spots at both Stanford StartX and Alchemist Accelerator. StartX provided the Stanford network and deep tech credibility. Alchemist brought enterprise go-to-market discipline and connections to B2B buyers. Together, they gave Fluence a launchpad that combines academic rigor with commercial execution.

Conclusion

Building Fluence is personal for Luciana. She saw the gap between AI capabilities and human understanding at Stanford, watched it persist across 50 countries at AB InBev, and decided to close it. Starting in Brazil, Fluence is building the behavioral intelligence infrastructure that every AI-powered platform needs. From São Paulo to the world.

👉 Explore how Fluence makes this possible →