CASE STUDYE-COMMERCE AUTOMATION

Scaling Multi-Channel Sales via AWS Serverless Architecture

How we transformed a fragmented manual inventory process into a high-performance, automated integration engine for a growing marketplace.

AWS LambdaNode.jsSupabaseOpenAI APIREST Sync

1. Overview

The client, a large-scale e-commerce aggregator, faced a critical bottleneck: managing inventory, pricing, and orders across five different marketplaces (Trendyol, Hepsiburada, Amazon, etc.) was purely manual. Every product update required 40+ minutes of manual labor, leading to frequent overselling and inconsistent pricing.

2. The Problem

  • Inventory desync leading to 15% cancellation rate due to out-of-stock items.
  • Manual SKU mapping taking 20+ hours per week of staff time.
  • Lack of real-time pricing strategy based on competitor movements.

3. The Solution

We developed a custom **Marketplace Integration Hub** built on a serverless event-driven architecture. The system acts as a central “brain” that synchronizes data bidirectionally between the master database and multiple marketplace APIs.

Automated Mapping

AI-powered SKU matching to link products across platforms automatically.

Real-time Sync

Sub-second inventory updates triggered by any sale or manual adjustment.

4. Architecture (AWS)

The platform utilizes a modern serverless stack to ensure zero maintenance and infinite scalability:

  • > AWS Lambda: Handles API logic and sync jobs.
  • > Amazon EventBridge: Orchestrates cross-platform events.
  • > Supabase (PostgreSQL): Real-time data storage & auth.
  • > OpenAI GPT-4: Cleans and translates product descriptions.

5. The Results

99%

Inventory Accuracy

-20 hrs

Manual Work / Week

0ms

Server Maintenance

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Tech Summary

IndustryE-commerce
CloudAWS (Serverless)
DatabaseSupabase
Time to Build4 Weeks

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