MFMaycon FerreiraAutomation · AI · Integrations
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CASE / INFINITY-ENGINE

CONFIDENTIAL CASE

Vesper Infinity Engine

AI-assisted generation

Private application to generate technical images and text using company context, visual standards and rules.

DECLARED ARCHITECTURE

CONTEXT AND RULES

This is a private application, so I only publish the architecture and flow — not screenshots of the internal interface.

PresetsStructured contextLocal memoryGemini
StateCONFIDENTIAL CASE
TechnologiesReact · TypeScript · Gemini · IndexedDB
What is publicConfidential case with sanitized architecture

ARCHITECTURE AND FLOW

How the system works

Sanitized representations of the architecture and control points — not screenshots of the private interface.
DECLARED ARCHITECTURE

CONTEXT AND RULES

This is a private application, so I only publish the architecture and flow — not screenshots of the internal interface.

PresetsStructured contextLocal memoryGemini
DECLARED ARCHITECTURE

APPROVAL BEFORE OUTPUT

Generation only moves to export or publication after human review.

DraftHuman reviewApprovalExport

What is represented

The cards describe components, rules and control points in the private flow without reproducing the interface or internal data.

Public version limits

Operational data, credentials, private integrations and client information are not part of this publication.

01

Context and problem

Industrial content must preserve technical context and identity without relying on an improvised prompt.

02

What I did

Interface, structured context, presets, local memory, Gemini integration and approval flow.

03

How I built it

React, TypeScript, Vite, Gemini and IndexedDB for history, preferences and settings.

04

Results and learning

  • All content requires review before export or publication.
  • Does not rely on traditional RAG; uses structured context and rules.

Limits of this version

Private application with no public demo.

Next steps

Evolution depends on the state and limitations described in this case; it is not presented as an already delivered capability.

The public version contains no credentials, personal data or sensitive internal information.

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