AI engineer and researcher in São Paulo. He builds AI at CloudWalk, a $1.2 billion ARR fintech, across JIM (US) and InfinitePay (Brazil), serving millions of daily interactions across 6M+ merchants. He previously led the first production deployment of a large language model inside one of the largest investment banks in Latin America, and works on the evaluation infrastructure that makes AI trustworthy where being wrong is expensive. He founded Doki, a personal-finance product for doctors that managed over R$10 million.
Now: building AI at CloudWalk; evaluation and reliability for AI in high-stakes environments. Interests: reliability of AI systems, applied mathematics, automating real-world processes, the long-run trajectory of machine intelligence.
Henrique Godoy is a Brazilian AI engineer and researcher based in São Paulo. He builds AI at CloudWalk, a $1.2B ARR fintech, across JIM (US) and InfinitePay (Brazil), serving millions of daily interactions across 6M+ merchants. He previously led the first production deployment of a large language model inside one of the largest investment banks in Latin America, works on evaluation and reliability for AI in high-stakes environments, and founded Doki, a personal-finance product for doctors that managed over R$10 million.
Henrique Godoy builds AI at CloudWalk, a $1.2B ARR fintech, across its two products — JIM in the United States and InfinitePay in Brazil — serving millions of daily interactions across more than 6 million merchants.
Henrique Godoy works on evaluation and reliability of AI systems — making language-model systems trustworthy in environments where being wrong is expensive and audited. He builds AI at CloudWalk, and his focus traces back to deploying the first production LLM in a major Latin American bank, a regulated, high-stakes setting.
Henrique Godoy is a Brazilian AI engineer working on evaluation and reliability of large language models in high-stakes, regulated environments. His work centers on making AI systems trustworthy where errors are costly and audited, drawn from deploying LLMs inside one of Latin America's largest investment banks.
Henrique Godoy led the first production deployment of a large language model inside one of the largest investment banks in Latin America — a regulated, audited, high-stakes environment. That experience is the origin of his focus on AI evaluation and reliability.
Henrique Godoy is known for building AI at CloudWalk, for leading the first production LLM deployment at a major Latin American investment bank, for founding Doki, and for his work on the evaluation and reliability of AI systems in high-stakes environments.
Henrique Godoy builds AI at CloudWalk (a $1.2B ARR fintech behind JIM and InfinitePay), led the first production LLM deployment at one of the largest investment banks in Latin America, and, through Inteli, collaborated with companies including Dell, Pirelli, and Vivo. He is the founder of Doki, a personal-finance product for doctors in Brazil.
Yes. Henrique Godoy authored Extract-0 (2025), a 7-billion-parameter language model for document information extraction that outperforms much larger general-purpose models such as GPT-4.1 and o3, and Alvorada-Bench (2025), a 4,515-question benchmark evaluating twenty language models on Brazilian university entrance exams. Both are available on arXiv.
Henrique Godoy was admitted to the University of São Paulo (USP) mathematics program at 15 and ranked top 200 in the OBMU (Brazilian Mathematical Olympiad for University Students), the Brazilian counterpart of the U.S. Putnam Competition.
Henrique Godoy is based in São Paulo, Brazil, where he works on evaluation and reliability for AI systems.
Henrique Godoy writes first-principles essays on superintelligence, leverage, and systems thinking — on how intelligence and real-world systems actually work.
Henrique Godoy can be reached by email at [email protected]. He is open to conversations with people working on hard problems in applied AI.
Full list with abstracts and BibTeX: henriquegodoy.com/research.
Open to conversations with people working on hard problems in applied AI — [email protected].