FreakingJSONJeisson Rojas · N30 / VectorES
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Maaji-IA

Client AI architecture

Maaji-IA is a client AI architecture that combines orchestration, data, and verifiable operations inside a real enterprise environment.

Maaji-IA — FreakingJSON
  • TypeScript
  • Node.js
  • Python

Context

The challenge was to connect ecommerce data, automation and decisions in a coherent AI architecture without adding operational fragility.

Constraint

The system had to run inside the client’s perimeter, respect internal policies, and never expose topology, credentials, or internal URLs in any public material.

N30’s role

I led the technical architecture as Lead AI Architect. I defined the boundaries, the permitted integrations, and the verification points for each sensitive flow.

System

Maaji-IA articulates agents, data, and operations into a verifiable architecture. Implementation details, internal topology, and operational scope are not published under client policy.

Evidence

The system has been in operation since late 2025. Public information is limited to its architectural nature and the role I played; no specific metrics are reported.

Result

A client AI architecture that runs with verification, audit, and clear boundaries between what is public and what is private.

This entry does not publish external links to honor the client’s confidentiality policy.