100,000+ Product Translations for 70 Markets with AI

The challenge

Parfois operates at a scale that breaks traditional localization workflows. With 1,000+ stores across 70+ countries, 5,000+ new SKUs every season, and new arrivals shipping weekly from design teams in Porto and Barcelona, the company needed every product to work across all markets simultaneously.

Volume meets velocity

The core issue was not translation quality in isolation, but the intersection of volume, velocity, and consistency.

Product titles needed to be compelling in Portuguese, Spanish, French, German, Arabic, and dozens more languages. SEO metadata had to perform differently in each regional search engine. Descriptions needed to resonate with customers in Dubai as naturally as in Lisbon.

Previous approaches fell short

Manual translation teams couldn't keep pace with product velocity. Basic machine translation produced technically accurate but commercially ineffective content.

Brand terminology drifted across markets. SEO performance varied wildly. Time to market stretched from hours to days.

The real cost wasn't translator fees. It was delayed launches, inconsistent brand voice, and missed visibility in key markets during critical selling windows.

Outcomes

Darkmatter built an AI translation engine in collaboration with Parfois, designed for the specific demands of high-volume retail localization.

Year one results

• 100,000+ product translations processed across all active markets
• Time to market reduced from days to hours for new product launches
• Consistent brand terminology maintained via auto-detected glossary and custom translation rules
• SEO-ready content generated for each market with proper URL slug translation and hreflang implementation

Toward Product Intelligence

Beyond operational improvements, the partnership surfaced a broader insight.

When AI processes product content at this scale, translation becomes a foundation for something larger: understanding how products perform linguistically across markets, identifying patterns in competitive positioning, and building the data infrastructure for market-specific optimization.

This is what we call Product Intelligence. Not a feature, but a shift in what becomes possible when product data is structured, multilingual, and AI-ready.

The outcome for Parfois is speed, consistency, and a foundation for continued optimization.

Technical approach

• AI translation pipeline with separate generation and editing stages for quality control
• Auto-detection of brand terms, product lines, and technical vocabulary for glossary management
• Custom translation rules to handle market-specific terminology and formatting requirements
• Integration with Parfois e-commerce infrastructure