Our Team

Tiago spent years in Cybersecurity using Network Analytics and Graph Theory to identify hidden relationships between threat actors (i.e. hackers) and detect patterns that were buried under layers of obfuscation. In cybersecurity, the challenge isn’t just identifying threats but doing so while attackers actively try to mislead detection systems by flooding networks with noise or exploiting weaknesses.

This taught him how to filter through massive amounts of data and isolate real threats.  In Finance the stakes are different, but the challenge is the same: cutting through the noise to find actionable insights. Financial markets, while more complex, are less adversarial by comparison - Instead of fighting obfuscation, the challenge is interpreting transparent data effectively. Tiago is now building systems that do just that, highlighting the hidden drivers of price movements and giving analysts a clear edge in decision-making.

It’s not about predictions, it’s about positioning yourself ahead of the curve, with concrete insights that can drive real results. That’s what excites him about this next phase: applying a proven approach to an entirely different set of challenges and seeing the tangible outcomes it delivers.He believes that Graph Theory, Complex Adaptive Systems and Agent-Based Modeling are underused methodologies in Finance.

These methods let us map and simulate the constantly shifting relationships that define markets, enhancing our ability to predict market shifts, track liquidity trends, and make smarter investment decisions. It’s a huge opportunity to push the boundaries of market analysis further and deliver real value for the industry.