Chicago, Illinois, United States
European technology companies rarely fail in the U.S. because of product quality. They fail because of early market positioning at the first credibility point, which determines classification, capital allocation, and the trajectory that becomes locked in. That positioning defines buyer profile, deal size, urgency, sales motion, and capital efficiency long before it appears in performance data. Early signals are consistently misread. Interest is treated as demand. Pilots are scaled without repeatability. Pipeline growth masks deterioration in buyer quality and commercial intensity. These distortions typically surface 18–36 months later, once capital has already been deployed, teams are in place, and the expansion path is difficult to unwind. For VCs, this is where companies shift from “future category leader” to capital-intensive execution risk at the exact moment additional capital is being considered. I work with European tech founders and investors on pre-capital U.S. expansion decisions, focused on the signals that determine whether capital is allocated into scalable growth or structural inefficiency. This is based on 500+ documented European expansion cases where early positioning, not product, determined outcomes before traditional metrics reflected it. The signal often looks like success. It is not. → exported.ai
Building a pre-capital risk infrastructure layer for EU–US expansion.
A decision-grade assessment of structural U.S. expansion risk before committing capital, hires, or GTM execution.
Operating inside U.S. commercial risk environments where pricing decisions, trust formation, and execution speed determine outcomes in real time. • Evaluated and priced $27M+ in annual commercial risk exposure across complex multi-party accounts with incomplete information under time pressure • Increased average bind rate from 41% to 63% through disciplined risk narrative construction and faster qualification-to-decision cycles • Closed 180+ high-value commercial submissions annually across brokers, carriers, and insured parties in competitive environments • Reduced projected loss ratios by 18% through pattern-based behavioral risk assessment across approved portfolios
Diagnosed why a competitive logistics operation was underperforming commercially - then rebuilt the entire GTM motion from the ground up using structured data, pipeline intelligence, and AI-enabled decision frameworks. Delivered $4.2M+ in new annual revenue and 28% overall territory growth through data-informed commercial strategy and disciplined account architecture. Closed enterprise accounts including Del Monte, Chiquita, and Oshkosh Defense - driving executive-level alignment on $1M–$5M+ annual contracts across complex, multi-stakeholder buying environments. Increased conversion rates by 34% and shortened average sales cycles by five weeks after rebuilding GTM processes from scratch — introducing buyer layer tracking, urgency scoring, and deal ownership visibility as core pipeline disciplines. Reduced stalled opportunities by 41% through AI-assisted pipeline frameworks that identified misclassified deals and wrong buyer layer engagement before capital was wasted on non-converting motions.
Three and a half years inside one of the most performance-pressured sales environments in the U.S. — building elite-level expertise in American buyer psychology, objection navigation, and high-stakes closing under sustained pressure. • Consistently exceeded annual quota by 135% on average — generating $480K+ in new premium revenue • Improved personal close rate from 18% to 31% through systematic refinement of objection navigation across complex, regulated sales conversations • Maintained 92% policy retention rate on closed business where credibility and long-term alignment were the decisive competitive factors • Trained and mentored 12+ sales representatives on closing architecture and execution discipline