The alternative is outsourcing the governance of its most sensitive data and its most critical decisions to foreign platforms operating under foreign law. For any regulated economy, that conversation is not theoretical. It is happening right now, at every bank, regulator, ministry, and university trying to move from pilot to production.
What is missing is not the model. It is the control plane around the model, the system that decides where AI runs, enforces compliance at execution, and logs every decision. That control plane does not exist yet. It is what we are building.
Jensen Huang is right: every company becomes an AI factory. What he leaves unanswered is who controls it, under whose law, on whose infrastructure, by whose rules. Saptiva AI exists so that the answer to each of those questions is: yours.
The founders of Saptiva AI spent thirteen years (2007–2020) building and operating Quiubas Mobile, bootstrapped with no venture capital and no institutional backing, until it became the messaging backbone across Latin America and was acquired by Twilio in 2020. Saptiva AI is what happens when the same team, with the same operating philosophy, starts again on a bigger problem.
Angel and Jesus Cisneros founded Quiubas Mobile and ran it for thirteen years. No VC. No institutional money. Just the patient work of operating carrier-grade infrastructure for banks, telecoms, and enterprises across 61 countries. By the time of the Twilio acquisition in 2020, Quiubas was the dominant messaging backbone across the region.
What this taught us matters more than the outcome. We learned how to operate mission-critical infrastructure at scale, under compliance regimes that do not forgive mistakes, for customers whose trust is earned in quarters and lost in minutes. We learned the real shape of doing business with regulated enterprises in Latin America.
After the Twilio acquisition, the obvious path was to step back. We saw something else: the same regulated enterprises we had spent over a decade serving began to ask a new question. How do we actually deploy AI, given what we handle and who watches us? The answer, in every conversation, was the same: nobody had built the control plane that made it possible.
Hyperscalers were optimized for US and EU compliance. Systems integrators were running project-based pilots that never compounded. Internal teams were stuck in multi-year builds. Every enterprise AI initiative was a one-off.
We started Saptiva AI to build what did not exist yet. Application layer that deploys in two weeks. frIdA orchestration engine that governs where AI runs and enforces compliance at execution. Infrastructure layer that operates across cloud, hybrid, on-premise, and air-gapped modes. One platform. One policy framework. Deployment mode as a runtime concern, not a replatforming event.
Today, Saptiva AI is in production across KAL (Mexico's first national-scale LLM, built with the Mexican government, validated by NVIDIA), Universidad Iberoamericana (Mexico's largest private AI lab), MultiMoney, and one of Mexico's leading insurance brokers. This is the beginning, not the end state.
Meet the team →We do not cite Quiubas to brag. We cite it because when an enterprise in this region is considering handing its AI infrastructure to us, the relevant question is not what we have promised. It is what we have actually operated.
We built Latin America's messaging backbone before APIs were standardized. We are building the control plane for regulated AI, wherever the law is hard.
Every product decision, every hiring decision, every customer conversation eventually lands on a principle. These are the ones we return to.
If you're an enterprise evaluating AI infrastructure, a technologist considering the team, or an institution thinking about what sovereign AI means in practice, there's a path in for each.
