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Fullstack E-Commerce Platform

GIO MANETTI E-Commerce

Private

Architected the system design, data modeling schemas, and AI agent execution plans for a comprehensive full-stack platform leveraging Next.js, Spring Boot, PostgreSQL, and Headless CMS integrations.

Project Overview

GIO MANETTI represents a modern, luxury e-commerce platform built to handle scale. This project involved designing the entire data schema from scratch and executing a full-stack implementation plan driven by AI agent workflows.

Luxury retail puts contradictory pressure on a storefront. Pages must be fast and indexable, which pushes work to the server; merchandising copy changes constantly, which pushes content out of the codebase; and inventory and payment must stay strictly consistent, which pushes transactions into a system that will not lose a write. Each concern was therefore given the tier that actually suits it rather than forcing one stack to do everything.

My work centred on the design layer rather than pixel-pushing. That meant modelling the entire schema from scratch — products, variants, media, stock, orders and customers as separate normalised entities with the relationships enforced by real constraints. A product is not a row: a single size can sell out without affecting its siblings, price history stays attached to the variant that carried it, and merchandising can reorder a collection without a data migration.

Between the storefront and the services sits a GraphQL / BFF layer that composes one response per view, which collapses page-load waterfalls into a single round trip and insulates the frontend from backend decomposition. Behind it, Spring Boot owns money and stock: checkout runs inside managed transactions so stock reservation, order creation and payment state move together or not at all — preventing the failure modes that actually matter in retail, like double-selling the last unit or recording an order without payment.

The implementation itself was executed through structured AI agent workflows. Each subsystem was specified as an explicit execution plan — data contracts, endpoint shapes, edge cases, definition of done — before any code was generated, so the output could be reviewed against a written specification rather than against intuition. That is what kept a fast build from turning into an inconsistent one.

Architecture & Engineering

  • Frontend built with Next.js & React for SSR and optimal SEO performance
  • Backend powered by Java Spring Boot for robust transaction handling
  • PostgreSQL database utilizing normalized schemas for inventory management
  • Headless CMS integration for dynamic marketing content
  • GraphQL / BFF (Backend-For-Frontend) layer to optimize client data fetching

Key Features & Highlights

  • End-to-end shopping cart and secure checkout flows
  • Dynamic product filtering and variant inventory management
  • Administrative dashboard for order monitoring and metrics
  • High-performance image serving and CDN caching

Technology Stack

Next.jsSpring BootPostgreSQLGraphQLHeadless CMS

Screenshots & Visual Artifacts

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Project Repository & Delivery

This repository is private due to client confidentiality, enterprise credentials, or proprietary intellectual property.

Private Repository
Open to Opportunities

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