Building LATAM’s First AI Unicorn How to Build Competitive Advantages in the AI Era

In May 2026, Enter, a São Paulo-based legaltech founded less than three years earlier by 26-year-old Mateus Costa-Ribeiro and two former Wildlife Studios executives, closed a US$100+ million Series B round led by Founders Fund, with participation from Sequoia, Ribbit, Kaszek, Atlantico, and ONEVC. At a US$1.2 billion valuation, the company became Latin America's first AI unicorn. EnterOS, the company's operating system for corporate legal departments, manages more than 300,000 lawsuits annually for Bradesco, Nubank, Mercado Libre, Airbnb, LATAM Airlines, and more than 60 other large enterprises in Brazil, the world's most litigious economy. Yet every capability Enter delivers rests on foundation models licensed from OpenAI, Anthropic, and Google, models that become cheaper and more capable each quarter and remain accessible to any competitor or customer. The case examines the economics of Brazilian mass litigation, traces Enter's journey from a Stanford dorm room to a Series B financing, and explores the four pillars of the founders' moat thesis: workflow integration, proprietary data, talent density and agent orchestration, and founder-market fit and trust. It asks how an application-layer AI company can build sustainable competitive advantage and avoid being "ChatGPTed away.

1-Understand how sustainable competitive advantage can be built at the application layer of the AI stack when the underlying foundation models are a rented commodity (the "ChatGPTed away" problem).
2-Analyse and critically assess the defensibility of four potential moats: workflow integration and switching costs, proprietary data, talent and execution, and trust and founder-market fit, and how they compound (or fail to) as models improve.
3-Examine how structural features of an emerging-market context (court fragmentation, litigation volume, and regulatory and institutional idiosyncrasies) create opportunities for local AI-native players that global incumbents (Harvey, Legora, Claude for Legal, and Gemini for Legal) have not built for: a leapfrogging opportunity for Latin America.
4-Discuss the strategic choices of a hypergrowth AI start-up: narrow focus versus horizontal expansion, "operating system" versus copilot positioning, an engineering-heavy operating model, and the role of venture capital in the Brazilian AI ecosystem.
5-Reflect on the broader implications of AI-driven automation for professional services, access to justice, and emerging-market competitiveness.