Key Moments
The Next Wave of AI Companies in Latin America | Tako CEO on The a16z Show
a16zKey Moments
Latin America has the talent and resources for AI global winners, but complex regulations and a lack of infrastructure make it tough. Tako is tackling Brazil's $20-$30 billion labor and tax complexity with AI to unlock unprecedented business potential.
Key Insights
Latin America, with 650 million people and significant engineering talent, is the third-largest economic block and possess the necessary infrastructure like GPUs and energy, yet faces immense business complexity.
Rappi, founded by Sebastian Mejia, became the first Latin American unicorn by acting as an 'operating system for local commerce,' scaling across nine countries and 300 cities.
Brazil's regulatory framework for labor and taxes is exceptionally complex, with some estimates suggesting it adds 10-20% to business costs or a total of $20-$30 billion in expenses, making effective management a critical challenge.
Tako has developed the world's only complete dataset of Brazilian labor regulations, which it uses to build AI agents that help companies navigate compliance and manage workforce operations from recruitment to payroll.
Mejia uses a talent assessment rubric based on IQ, EQ, AQ (Adversity Quotient), and Energy, emphasizing resilience and hardship stories to identify globally great talent, not just locally.
The Central Bank of Brazil is highlighted as a highly innovative entity, exporting its expertise in payment systems (like PIX) and blockchain regulation globally, contributing to Brazil's technological advancement.
Navigating complexity: The Latin American opportunity and challenge
Latin America represents a massive economic bloc with 650 million people, engineering talent, abundant energy, and biodiversity. However, the region, particularly Brazil, is plagued by extremely complex regulatory frameworks, significantly increasing the cost of doing business. Some estimates suggest this complexity adds 10-20% to business costs, translating to billions of dollars lost annually in managing labor and tax issues. Sebastian Mejia, founder of Rappi and now Tako, believes that building systems to effectively manage this complexity is key to unlocking unprecedented potential for companies in the region. This inherent difficulty, while challenging, also creates opportunities for durable and defensible businesses. So what? Overcoming regional complexity is not just a hurdle but a strategic advantage, creating strong moats for companies that can master it.
From Rappi's hyper-growth to tackling Brazil's regulatory maze
Mejia's entrepreneurial journey includes co-founding Rappi, which he scaled into a super-app described as the 'operating system for local commerce' across nine countries and 300 cities. Rappi's success was built on mastering complex logistics and providing delivery services for groceries, restaurants, and liquor in minutes. This experience in operating in a challenging, multi-vertical, low-margin, and competitive environment made Rappi's team 'battle-hardened operators.' After nearly a decade, Mejia transitioned to start Tako, an AI company focused on solving the immense labor and tax complexities in Brazil. Tako aims to build AI agents that understand and process all labor regulations, supporting companies in managing their workforce operations. This focus on deep complexity and proprietary data sets aims to create a highly defensible business. So what? The lessons learned from building a complex operational business like Rappi provide a strong foundation for tackling even more intricate problems with AI.
Tako's AI engine: Mastering Brazilian labor law with proprietary data
Tako's core mission is to create an intelligence layer for companies to manage their workforce operations using AI. A significant achievement is the development of a complete dataset of Brazilian labor regulations, a feat claimed to be unique globally. Brazil's labor laws are notoriously intricate, stemming from constitutional mandates, judicial decisions, and regional variations, often leading to contradictions and frequent changes. Mejia likens the situation to 'humans as a service' (HAS), where businesses rely heavily on manual processes to navigate these regulations. Tako aims to replace these low-value, complex services with AI agents. One product, 'Auto,' functions as an 'open evidence for labor' system, offering benchmarks superior to general LLMs and helping companies assess compliance. Failure to comply can result in significant financial penalties. Other agents handle recruitment, onboarding, payroll, government integrations, and employee offboarding. These solutions target medium to large enterprises struggling with an estimated $20-30 billion in costs associated with labor and tax compliance in Brazil. So what? By owning and processing the most comprehensive data on Brazilian labor law, Tako is building a defensible AI solution that can fundamentally transform how businesses operate in a highly regulated market.
Talent acquisition: The 'diamond' rubric and global perspective
Mejia emphasizes a unique approach to talent acquisition, driven by his experience as an immigrant and having lived and built companies globally. He believes in identifying 'globally great' talent, not just 'locally great.' His interview process delves into candidates' childhoods, resilience, and hardship stories, looking beyond standard qualifications. Mejia uses a 'diamond' rubric assessing IQ, EQ (Emotional Intelligence), AQ (Adversity Quotient/Resilience), and Energy (or agency – persistence in problem-solving). At the center is 'heart,' representing high integrity, values, and trust. This rigorous evaluation aims to find individuals who are not only intelligent and emotionally adept but also resilient and driven, especially crucial for tackling difficult problems. Tako has even opened a 'hacker house' in Silicon Valley to connect its engineers with cutting-edge AI research and talent. So what? A deliberate, deep-dive approach to talent, focusing on fundamental traits beyond resumes, is critical for building high-performing teams capable of tackling complex, global challenges.
Brazil's regulatory innovation and the 'misunderstood' central bank
Despite being perceived by some abroad as a purely emerging market, Brazil possesses highly sophisticated regulatory frameworks and institutions. The Central Bank of Brazil is highlighted as a prime example, leading in innovation not only with PIX but also in utilizing blockchain for regulatory purposes. The bank's technical prowess and expertise are being exported globally. Furthermore, Brazil's competition regulatory body is described as extremely sophisticated and technocratic. A key asset is 'eSocial,' a central repository that logs events for approximately 10 million companies and 60 million employees, covering hiring, payroll, holidays, and time off. This granular data allows for rapid company onboarding, as Tako can onboard clients in mere days. Money movement and tax filing are also streamlined, with tax processes being largely prepared for simple digital sign-off. This modern infrastructure, while existing alongside complexity, offers significant advantages. So what? Brazil's advanced regulatory infrastructure, often overlooked, provides unique opportunities for technology companies that can effectively leverage it, accelerating adoption and innovation.
The AI opportunity and the path to global leadership from Latin America
Mejia argues that the AI opportunity in Latin America is doubly significant because the region, having previously skipped widespread adoption of traditional software due to cheaper labor, can now leapfrog directly into AI-driven solutions. This presents a chance not just to replace software and labor, but to fundamentally modernize industries that are 15-20 years behind. For Latin America to produce global AI winners, companies must focus on building 'durable' businesses with strong defensibility, which can arise from intellectual property (IP), scale, network effects, or switching costs. He stresses the importance of developing a sovereign AI stack, including local GPU clusters and fine-tuning proprietary models, to avoid over-reliance on foreign infrastructure. Investing in research, maintaining a 'world garden' of data, and fostering continuous learning among engineers are crucial. The ultimate goal is to apply AI to solve real-world problems, explainable in layman's terms, rather than focusing on the technology itself. Companies that embrace quality and aim for global greatness, despite the inherent difficulties in the region, are most likely to succeed and contribute to modernizing the economy, potentially impacting GDP growth positively. So what? The combination of a vast underserved market, the potential for AI-driven leaps, and the development of robust, defensible business models is the key to unlocking global AI leadership from Latin America.
Mentioned in This Episode
●Software & Apps
●Companies
●Organizations
●Books
Common Questions
Latin America faces significant challenges including complex regulatory frameworks, high costs of doing business, and a historical reliance on cheaper labor over technology adoption. Seas highlights that Brazil, for example, has some of the most complex regulations globally, creating a hostile environment for businesses.
Topics
Mentioned in this video
A client of Seas's previous company, whose work in India inspired him to see the possibilities of applying technology to emerging markets.
Delivery app and super app founded by Seas, becoming the first Colombian unicorn and operating across nine countries and 300 cities in Latin America.
Seas's current company, building an intelligence layer for companies to manage workforce operations using AI agents that understand labor regulations.
Mentioned as an example of a company with a hard business model that fosters incredibly talented entrepreneurs.
A highly admired US company from which Seas recruited talent for Rappy, bringing valuable operational lessons.
Seas's home country, where he founded Rappy, which became the first Colombian unicorn.
City in Spain where Seas moved at 17-18 years old, experiencing significant life changes and becoming more of a 'person of the world'.
City Seas moved to in 2009 after the financial crisis. He spent five to six years there, building companies, meeting his wife, and finding investors.
The first market where Rappy launched its delivery service in October 2015.
A market Rappy expanded to early in its history, contrary to investor advice, highlighting the importance of being in scaled markets.
A focus country for Taco, known for its complex labor and tax regulations, which Taco aims to simplify with AI. It's also noted for its innovative central bank and regulatory bodies.
Noted for its innovation in fintech, adoption of blockchain, and sound regulation, even exporting its models to other countries.
A museum in Paris with an 'inside out' architectural design, used as a metaphor for Taco's approach to building understandable AI agents.
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