Methodology
This report combines quantitative and qualitative research methods to provide a comprehensive overview of the Deep Tech ecosystem in Latin America.
# Quantitative approach
We began with a dataset of 5,000 Deep Tech companies from LATAM, sourced primarily from Tracxn. After a review process, we retained ~2,500 companies for our final analysis. The data cutoff date was March 2025. To assist with accuracy in classification, we employed large language models (LLMs) for initial categorization, supplemented by meticulous manual validation.
For the manual checks, our team reviewed open-source materials, including patents, scientific publications, documentation, and corporate disclosures, to verify whether companies met established criteria for Deep Tech classification. The primary challenge involved distinguishing companies that leverage trendy technologies like Artificial Intelligence primarily as superficial marketing strategies from those genuinely developing novel, scientifically rigorous solutions.
Another critical obstacle was the lack of a shared, comprehensive, and openly accessible regional database. During our literature review, we found that existing reports frequently rely on proprietary datasets or private data brokers, limiting their value as a universally acceptable benchmark for ecosystem mapping. It is important to note that this is not an exhaustive database, but the most complete mapping we have seen to date.
To classify the companies by Deep Tech vertical, we took the 12 categories proposed by the 2023 Deep Tech: The New Wave report, backed by the Inter-American Development Bank: Robotics, Spacetech, Advanced Mobility, Biotechnology, Blockchain, Artificial Intelligence, Cleantech, Advanced Materials, Healthtech, Infinite Computing, Advanced Manufacturing, and Nanotechnology. To classify the companies by industry, we took the 8 categories proposed by EMERGE’s 2024 Relatório Deep Tech Brasil: Agribusiness & Animal Health, Food & Beverages, Cosmetics & Wellness, Energy, Chemicals, Petrochemicals & Materials, Human Health & Pharmaceuticals, Sustainability & Environment, and Other.
# Qualitative approach
Our qualitative research consisted of 5 roundtables and 100+ interviews with stakeholders across the ecosystem, including founders, investors, accelerators, researchers, and government actors. We asked them: what key gaps make LATAM investment less attractive to global VCs, and which resources would help bridge that gap? What do investors in LATAM’s Deep Tech ecosystem look for when deciding to fund startups at both the regional and global levels? How would you design a regional coalition that bridges local startups with global investment?
This report synthesizes insights from these conversations without attributing specific comments. We applied an obstacles-first lens to surface the binding constraints blocking ecosystem transformation, grounding our recommendations in removing root causes rather than proposing generic, solution-first fixes.