Brazilian-American executive, systems designer, and writer — four decades spent building the financial and operational architecture of industrial companies from the ground up, across several countries.
My career has centered on a specific and unusual mandate: holding CFO, CIO, and CTO responsibilities simultaneously, across multinational industrial operations in several countries — most often in greenfield environments, where the financial, technological, and operational architecture had to be designed and installed from nothing.
Alongside that executive work, I have founded five companies, four of which succeeded, and led turnaround mandates in operations characterized by second-generation family business deterioration — the specific, recurring pattern where a founder's discipline erodes by the time control passes to the next generation, and where the financial and governance rebuild has to happen without stopping the business underneath it.
I am Brazilian-American, based between Oakland, California and São Paulo, Brazil, and I bring a secular humanist framework and a lifelong commitment to anti-corruption work to everything I structure, write, and advise on.
I designed and implemented one of my career's defining systems at Votorantim's pulp-and-paper operations: an industrial automation architecture spanning more than 45,000 instrumentation points, built on a biologically-inspired distributed cognition model rather than a single centralized controller — a design philosophy I return to whenever a system needs to keep functioning even when one part of it fails.
That same philosophy — never overwrite a system's safety-critical core — has carried through every automation and turnaround mandate since, including a period consulting on Waymo's autonomous vehicle program, where I insisted on hands-on transit bus driver training to ground the design work in a real, lived safety culture rather than a theoretical one.
I built a structure to capture automation data specifically to optimize maintenance — turning routine equipment signals into an early-warning system rather than a historical log. The same underlying data pipeline didn't stop at maintenance: I extended it to capture real cost information directly from the automation layer and feed it into a sales order system, restructured to maximize profit participation on every individual order rather than pricing off an average cost that hides which orders are actually profitable.
The same discipline has applied directly to business recuperation work — restructuring finance and operations under real time pressure specifically to avoid bankruptcy, not just to improve margins.
My AI work has always been applied, not theoretical. I built a predictive model originally targeting inflation forecasting, and pivoted its use toward stock market analysis once that proved the stronger application of the same underlying architecture — treating the model as a tool to be pointed at whichever problem it actually solved best, rather than forcing it to fit its original brief.
That same instinct drives my ongoing research into cognitive AI — how these systems reason, where that reasoning breaks down, and what that means for using them as genuine decision-support tools in finance and operations rather than as a narrative device for a board deck.
Every greenfield mandate I take on follows a disciplined sequence — financial architecture and technology infrastructure built together, in the right order, so nothing has to be re-engineered later under pressure.
This is where the full six-step greenfield CFO methodology from the Page Executive portfolio belongs — send over the steps and I'll lay them out in the numbered format below, matching the site's typography.
You've documented two greenfield case studies for the portfolio process — a China milk-processing facility build and a Brazilian dual-division industrial manufacturing launch. Send over the narrative details (scope, timeline, your role, the outcome) and I'll write these up as proper case-study cards matching the rest of the page.
Treasury, fiscal compliance, controllership, and risk architecture built for auditability and scale from day one.
ERP selection and implementation, data warehousing, and automation that gives finance a real-time view of operations.
Large-scale, distributed-authority automation design — instrumentation at the scale of tens of thousands of points, without a single point of failure.
Rebuilding financial and governance discipline in operations weakened by generational transition or real bankruptcy risk, without stopping the business underneath the rebuild.
Capturing cost data straight from the automation layer to optimize maintenance and restructure sales orders around real per-order profit participation.
Active researcher since 1984 — predictive modeling pivoted from inflation forecasting to stock analysis, and ongoing research into how cognitive AI systems actually reason.
Long-form analysis of capital concentration, monetary architecture, and institutional capture, published with full AI-collaboration disclosure.
"Never overwrite a system's safety-critical core."— Design philosophy, carried from industrial automation into every mandate since