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Flat Magic

Flat Magic: Amazon Product Variation Detection

AI-powered Amazon product analysis. Automatic product variation detection with Gemini AI.

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www.flat-magic.com
Flat Magic: Amazon Product Variation Detection – Project preview
Case Study

The Problem

Amazon sellers face a time-consuming task: manually identifying and correctly grouping product variations. With thousands of listings, this process is error-prone, inconsistent, and eats up valuable working hours. Incorrect variation assignments lead to listing errors, poor visibility, and lost sales.

Manual creation of Amazon Flat Files is a bottleneck that slows growth.

The Solution

Flat Magic analyzes product data from Excel files and automatically detects variation relationships between products. Instead of manually reviewing each product, sellers upload their data and receive AI-generated variation groups in minutes instead of hours.

The Gemini AI algorithm understands product attributes, recognizes patterns, and suggests matching variation themes.

Features

Excel Upload and Processing

Sellers upload their product data as an Excel file. The system automatically processes the data and extracts relevant product attributes for analysis.

AI-Powered Variation Detection

The Gemini AI algorithm analyzes product properties and automatically identifies which products are variations of each other. Color, size, material, and other attributes are intelligently grouped.

Visual Product Grouping

Detected variation groups are displayed in a clear overview. Sellers can review, adjust, and confirm assignments before exporting.

Amazon Flat File Export

The result: an Amazon-compliant Flat File ready to upload directly to Seller Central. No manual formatting, no errors.

Batch Processing

Large product catalogs are processed efficiently. Instead of product by product, thousands of listings can be analyzed simultaneously.

Results

  • Hours saved: Automated variation detection replaces manual product data maintenance
  • Fewer errors: AI-based analysis significantly reduces assignment mistakes
  • Faster time to market: New products are correctly listed more quickly
  • Scalability: Large catalogs are processed just as efficiently as small ones
Results

Automated flat file generation saves hours of manual product data maintenance

End of case study
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Jamin Mahmood-Wiebe

Jamin Mahmood-Wiebe

Managing Director

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