Jelou Secures $10M to Transform WhatsApp Into a Transactional AI Platform

Jelou has raised a $10 million Series A to expand its platform for building AI agents that execute real business and financial operations directly inside WhatsApp conversations. The company, which operates out of New York and Quito, is focused on a simple but difficult problem: while messaging has become the dominant interface between businesses and customers, the actions that actually move money still happen elsewhere.

Payments, identity verification, credit applications, and signatures are typically pushed into portals, forms, or call centers, creating friction and abandonment at the moment customers are most ready to act. Jelou was built to close that gap by allowing AI agents to complete transactions inside the conversation itself.

The round was led by Wellington Access Ventures, with participation from Krealo, Credicorp’s corporate venture arm, and Collide Capital. With this raise, Jelou has secured $13 million in total funding, following a $3 million seed round led by Act One Ventures and Arca Continental Ventures.

From Conversations to Execution

Conversational channels like WhatsApp are already the default way businesses interact with customers across much of Latin America. Yet most AI tools operating in these environments are limited to answering questions or routing requests. Jelou’s approach focuses instead on execution—connecting conversational AI directly to enterprise systems so work can move forward without leaving the chat.

At the center of this strategy is Brain, Jelou’s platform for building and operating transactional AI agents. Through Brain, businesses can deploy agents that collect information, verify identity, trigger payments, and advance financial workflows using live system data. These agents operate inside WhatsApp while integrating with existing infrastructure, allowing companies to automate complex processes without introducing new security or compliance risks.

The platform includes a web-based studio with more than 3,000 integrations, along with a conversation management layer that allows teams to supervise high-volume interactions while sensitive operations—such as payments, underwriting, or document signing—are executed securely.

Built in Regulated Environments

Jelou’s origins trace back to Ecuador in 2017, where founder Luis Loaiza and the team observed a widening disconnect between how people communicated with businesses and how transactions were actually completed. Messaging was ubiquitous, but execution remained fragmented and often insecure.

Drawing on experience building encrypted messaging systems, the team set out to make chat a place where real business happens. That focus on production-grade systems shaped Jelou’s early deployments in regulated banking environments, where security, auditability, and reliability are non-negotiable.

Since then, Jelou has expanded across Latin America, serving more than 500 businesses in over 13 countries. Its AI agents have processed more than $100 million in financial operations for customers spanning banking, retail, logistics, and consumer goods—industries where conversion and operational efficiency are tightly linked.

Why Transactional AI Is Different

Jelou’s growth reflects a broader shift in how companies are thinking about AI adoption. Automation only delivers value when it is tightly integrated with existing systems and capable of driving real outcomes. In regions with diverse regulations, payment rails, and legacy infrastructure, conversational AI that cannot execute transactions offers limited upside.

By embedding execution directly into messaging channels, companies can reduce friction while also shortening operational loops. At the same time, this shift raises new requirements: AI agents must operate with clear governance, traceability, and safeguards, especially when handling financial actions.

Jelou Raises $10M to Build AI Apps That Move Money on WhatsApp

Jelou’s Series A highlights how transactional AI is beginning to move from experimentation into infrastructure. The company’s experience in regulated Latin American markets demonstrates that messaging platforms can support real financial execution when designed with compliance and system integration at the core.

More broadly, this model signals a change in where transactions happen. As AI agents become trusted intermediaries between users and enterprise systems, messaging apps start to function less as communication tools and more as transactional layers. Payments, account creation, and credit decisions no longer need to be routed through separate applications—they can occur in the same conversational context where intent is formed.

This shift suggests that the future of AI-driven transactions will depend less on conversational polish and more on reliable execution. As businesses look to reduce friction and operational cost, platforms that allow AI agents to move money securely inside familiar channels may redefine how financial interactions take place across the Americas and beyond.