Geraldo.Gonçalves
System Map
Case File N1 / 03Status: Complete

Frontend Development

Web & Mobile

Real-time AI experiences and large-scale interface consolidation, shipped across web and native mobile.

Measured

M1

0ms

target latency on AI-to-human handoff

M2

20+

microfrontends refactored and merged

M3

-3

clicks per section, average

M4

0

key navigation bottlenecks left unresolved

§01

Real-Time AI Customer Service

Developed a real-time AI customer service system for a government client, enabling zero-latency AI-to-human handoffs and automated database querying. The hard constraint in a handoff like this is state: when a conversation moves from an AI agent to a human operator, the full context and query results have to already be there. A zero-latency handoff is a promise that the human never has to ask the citizen to repeat themselves.

§02

Native Payments & Loyalty

Implemented native payment integrations and a loyalty system for a cross-platform marketplace, improving transactional flow and rewards conversion. Native payment integration means working against the platform's own payment APIs and constraints rather than a generic web checkout. The loyalty logic then had to sit on top of that transactional layer without adding friction to the moment someone is already trying to pay.

§03

Navigation Redesign

Redesigned user flows and interface, reducing the average number of clicks per section by 3 and eliminating key navigation bottlenecks. Getting a click count down by a consistent margin across sections, not just one screen, means the fix was structural: a rethought information architecture, not a single shortcut button bolted onto an existing flow.

§04

Microfrontend Consolidation

Refactored and merged more than 20 microfrontends to integrate a national car toll system, improving maintainability and reducing duplication across teams. Twenty-plus independently built microfrontends accumulate divergent patterns, duplicated components, and inconsistent state handling by default. Consolidating them across teams is an exercise in reading everyone else's assumptions and finding the shared architecture underneath.

Components

T1ReactT2React NativeT3TypeScriptT4WebSocketsT5NLP APIsT6Node.js