Captixy
About

A product built from curiosity, research and real-world iteration.

Captixy started as a personal exploration into AI agentic development and AI engineering. Over time, that curiosity evolved into a practical product, refined through experimentation, personal work, and feedback from customers who saw value in the solution.

JR

João Rodrigues, Founder

João Rodrigues is the creator of Captixy and a software engineer with more than 10 years of experience working across solution architecture, pre-sales, business development, management and IT team leadership. Throughout that path, he has operated at the intersection of technology, commercial strategy and execution, building a practical understanding of how products need to create value in real operating environments. In recent years, he has intensified his work in AI engineering, agentic systems and applied automation design, bringing that expertise into a product built to turn real conversations into qualified, actionable context.

How the idea started

The project did not begin as a business-first initiative. It started as a personal investigation driven by curiosity, taste for building, and a genuine interest in understanding what modern AI systems could do when applied in an agentic, product-oriented way.

As João explored AI through personal work, prototypes and iterative experiments, the idea became clearer: there was room for a product that could make inbound conversations more structured, more useful and easier to act on without taking control away from the person using it.

From exploration to product

Captixy was developed across multiple iterations. Each version improved the product's understanding of replies, the way context was structured, and how automations could support the user without feeling generic or intrusive.

What began as personal R&D gradually turned into a product with customers who recognized the value of the approach and the solution being proposed.

What Captixy is today

Today, Captixy is a product focused on helping an individual consultant or agent manage social conversations with more clarity. The user defines the automation flow, and AI helps by interpreting replies, qualifying contacts and organizing context so the next action is easier to decide.

Founder-ledBuilt directly by the person behind the original research and product iterations.
AI-nativeDesigned around interpretation, qualification and context instead of AI for its own sake.
Iterative by natureShaped through ongoing experiments, real usage and repeated refinement.
Built for practicalityCreated to solve a real workflow problem in a way that feels useful from day one.
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