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a16z Podcast

The Fintech Playbook for Latin America

48 min episode · 2 min read
·

Episode

48 min

Read time

2 min

Topics

Productivity, Startups, Fundraising & VC

AI-Generated Summary

Key Takeaways

  • Monorepo architecture as AI foundation: Adi built on a single-code monorepo rather than microservices — a contrarian choice when microservices dominated. This decision means all code is readable by AI agents in one place, enabling faster deployment. Paired with event-sourcing via Kafka and Databricks, the system processes 10 million+ daily events queryable in real time for LLM consumption.
  • Start AI deployment with hardest use case first: Rather than beginning with customer service like most companies, Adi launched AI with legal response automation — Colombian law requires constitutional lawsuit responses within 48 hours or the CEO faces jail. Building those data pipelines first meant customer service agents reached 60% full resolution immediately at launch, versus a slower ramp from easier starting points.
  • North Star metric over OKR cascades: Replace sprawling OKR frameworks — which can generate 25+ tracked items — with one to three L1 metrics the entire company can name. Adi sequenced through risk-adjusted margin, gross margin, gross margin minus sales and marketing, then EBITDA. This single-metric focus drove Adi from losses to profitability and kept weekly business reviews actionable.
  • Remote-first operations accelerate AI adoption: Running a remote company forces all context to be written explicitly rather than shared verbally. This creates structured APIs and documented SOPs that AI agents can directly consume. Adi currently operates 150 headcount below budget while exceeding growth targets, attributing the efficiency gap directly to agents operating on this explicit written-context infrastructure.
  • Contrarian market selection over consensus geography: Most Latin American fintech founders target Brazil or Mexico first. Adi chose Colombia — then considered too cash-dependent (65-70% cash transactions, under 20% credit card penetration) — because smartphone adoption surged from elite to mass-market between 2014 and 2016, creating zero-marginal-cost distribution. Focusing deeply on one country rather than spreading thin across markets mirrors Kaspi's Kazakhstan playbook.

What It Covers

Santiago Suarez, founder and CEO of Colombian fintech Adi, details how his company scaled to 3 million consumers and 50,000 merchants by combining buy-now-pay-later, payments, logistics, and banking — while deploying over 200 AI agents that handle 100% of customer service queries with 80% full resolution rates.

Key Questions Answered

  • Monorepo architecture as AI foundation: Adi built on a single-code monorepo rather than microservices — a contrarian choice when microservices dominated. This decision means all code is readable by AI agents in one place, enabling faster deployment. Paired with event-sourcing via Kafka and Databricks, the system processes 10 million+ daily events queryable in real time for LLM consumption.
  • Start AI deployment with hardest use case first: Rather than beginning with customer service like most companies, Adi launched AI with legal response automation — Colombian law requires constitutional lawsuit responses within 48 hours or the CEO faces jail. Building those data pipelines first meant customer service agents reached 60% full resolution immediately at launch, versus a slower ramp from easier starting points.
  • North Star metric over OKR cascades: Replace sprawling OKR frameworks — which can generate 25+ tracked items — with one to three L1 metrics the entire company can name. Adi sequenced through risk-adjusted margin, gross margin, gross margin minus sales and marketing, then EBITDA. This single-metric focus drove Adi from losses to profitability and kept weekly business reviews actionable.
  • Remote-first operations accelerate AI adoption: Running a remote company forces all context to be written explicitly rather than shared verbally. This creates structured APIs and documented SOPs that AI agents can directly consume. Adi currently operates 150 headcount below budget while exceeding growth targets, attributing the efficiency gap directly to agents operating on this explicit written-context infrastructure.
  • Contrarian market selection over consensus geography: Most Latin American fintech founders target Brazil or Mexico first. Adi chose Colombia — then considered too cash-dependent (65-70% cash transactions, under 20% credit card penetration) — because smartphone adoption surged from elite to mass-market between 2014 and 2016, creating zero-marginal-cost distribution. Focusing deeply on one country rather than spreading thin across markets mirrors Kaspi's Kazakhstan playbook.

Notable Moment

Suarez described flying to Kazakhstan after four unanswered LinkedIn messages to meet Kaspi's CEO, who advised him to ignore equity investors for up to a decade when building a deeply integrated single-country platform — predicting they would eventually ask why he never called.

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Episode Transcript

Don't let your ambition fall prey of commercial wisdom. If you're a consensus play, there's just no alpha. We serve over 3,000,000 consumers, over 50,000 merchant partners. We have incredible cost to serve economics, over 200 agents in production. We built a company on a monorepo as opposed to microservices. Monorepos today are all the rage. Anthropics built on a monorepo. Google, obviously, famously is a monorepo company. When we started the company, microservices was where it was at. So why did you make the decision? What gave you the forethought to make it? I hired the best CTO in the business. How did you get your organization culturally moving as quickly as you have? It's basically a combination of two things. We have a very clear view of where we are and where we wanna be. We have been extremely explicit with folks about standards and expectations. It's not going to be easy. It hasn't been easy, but Building a technology company in Latin America often means solving problems that don't exist elsewhere. Fragmented financial infrastructure, limited access to credit, and underdeveloped software systems create challenges, but also opportunities to rethink how commerce and financial services work. Over the last several years, Adi has grown from a buy now, pay later product into a broader platform spanning payments, commerce, logistics, and banking. Angela Strange and Gabriel Vasquez speak with Adi founder and CEO Santiago Suarez about financial inclusion, technology We're here today with Santiago Suarez, the founder and CEO of Adi. Adi is a buy now, pay later marketplace and payments platform in Colombia, and now just recently a bank. And Adi has served over 25% of the population. Welcome to the show. Thrilled to be here. Amazing. Thank you. Alright. So for those in our audience who may be less familiar with Adi, can you give us a sense of what does the company do now and what scale are you at? Absolutely. So we provide consumers and merchants with financial solutions such as credit at the point of sale, instantaneous payments, logistics. We just got our banking license. So you should think of it as the kind of elemental fabric of commerce and financial services in one of the fastest growing Latin American economies. Size wise, we serve over 3,000,000 consumers or 50,000 merchant partners. That's a little bit about the scale of Adi and what we do today. Okay. So we're gonna talk a lot about Adi. I think it's interesting to talk about your career pre Adi. So you're from Columbia. You came to The US to go to college. You joined the startup as a first employee, and you're pretty public about being fired from said startup. And then left, very surgically created a list of the 10 best operators in your mind, and you wanted to go work for one of those. Yep. And you chose Jamie Dimott. So maybe walk us through the lessons from those experiences that relate to what you're …

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Tools

  • by Apache

    Paired with event-sourcing via Kafka and Databricks, the system processes 10 million+ daily events queryable in real time for LLM consumption.
  • by Databricks

    Paired with event-sourcing via Kafka and Databricks, the system processes 10 million+ daily events queryable in real time for LLM consumption.

company

  • AdiBy guest
    Santiago Suarez, founder and CEO of Colombian fintech Adi, details how his company scaled to 3 million consumers and 50,000 merchants by combining buy-now-pay-later, payments, logistics, and banking — while deploying over 200 AI agents.
  • Focusing deeply on one country rather than spreading thin across markets mirrors Kaspi's Kazakhstan playbook. Suarez described flying to Kazakhstan after four unanswered LinkedIn messages to meet Kaspi's CEO.

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