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Case Study

Naratix : Intelligent AI Agents for Global Multilingual E-Commerce Content


Retail & E-commerce

Naratix – AI Agents for Multilingual E-Commerce Content

We collaborated with Naratix to build multilingual AI agents that generate and manage product content for global e-commerce brands. These AI agents automatically create titles, product descriptions, and meta tags in multiple languages, fine-tuned for local markets and SEO. Using a blend of sentiment analysis, NLU, and brand tone modeling, the system localizes messaging to resonate with specific customer segments. Integrated with CMS and product catalogs, it ensures real-time updates for thousands of SKUs across regions. This intelligent content automation not only scaled their global presence but also helped Naratix clients rank better and convert faster.

Project Overview

  • Client: Naratix (E-commerce automation platform used by 200+ global brands)
  • Challenge: Inconsistent product messaging across languages + slow manual content translation
  • Goal: Deploy multilingual AI agents to:
    • Automate content creation for 10K+ SKUs in 14 languages
    • Maintain brand tone, emotional relevance, and SEO accuracy
    • API-first CMS and multi-PIM system integration
  • Team: 6 (2 NLP Engineers, 2 Integrators, 1 SEO Strategist, 1 QA Specialist)
  • Timeline: 4.5 months (MVP → Regional pilots → Global rollout)

“Our global content used to take weeks—now, with GenX AI agents, it takes hours. And it resonates better. Our clients are seeing the difference.”

Chief Automation Officer, Naratix

The Challenge

Critical Pain Points:
  • Manual content localization delayed product launches in non-English markets
  • Regional SEO variations hampered natural visitor acquisition
  • Lack of emotional resonance in auto-translated descriptions hurt conversions
Technical Hurdles:
  • Maintaining contextual tone and brand personality across 14 languages
  • Adapting SEO metadata dynamically based on regional search behavior
  • Real-time sync with multiple CMS, PIM, and e-commerce platforms

Tech Stack

Component Technologies
NLG Models OpenAI GPT-4, MarianMT, LangChain
SEO Optimization SEMrush API, Ahrefs API, ElasticSearch
Backend + Integration Python, FastAPI, Webhooks, RabbitMQ
Cloud Infrastructure AWS (Glue, Step Functions, S3, Lambda)
CMS & PIM Integration Shopify, Magento, Contentful, Pimcore
Monitoring CloudWatch, Sentry, Grafana

Key Innovations

The AI agents created 10,000+ localized product descriptions across 8 languages with SEO-rich metadata. Tone customization ensured brand alignment in every market. Bulk updates were handled in real-time across SKUs, saving time and boosting global ranking.

Localized AI Content at Scale

  • Created 10K+ product descriptions in 14 languages with cultural precision

Result: 62% faster go-to-market in international campaigns

SEO-First Meta Engine

  • Optimized metadata for region-specific SERPs and keyword density

Result: 37% increase in organic impressions within 6 weeks

Emotion-Aware Brand Messaging

  • Tone tuned to resonate emotionally across different cultures

Result: 22% uplift in conversion rates for luxury fashion clients

Our AI/ML Architecture

Core Models

  • Multilingual Content Generator:
    • GPT-based NLG pipelines with translation validation layers
    • Fine-tuned on 5 years of brand-specific multilingual copy
    • Controlled tone settings (formal, friendly, luxury, etc.)
  • SEO-Driven Metadata Engine:
    • Integrated SEMrush + Ahrefs APIs for keyword targeting
    • Region-aware meta tag generation and optimization
  • Emotion & Tone Modulator:
    • Sentiment analysis + cultural tone mapping
    • Dynamic vocabulary selection based on user psychology data

Data Pipeline

  • Sources
    • Product catalogs from Shopify, Magento, and BigCommerce
    • Regional SEO keyword datasets
    • Brand tone and vocabulary models (provided by clients)
  • Processing: Automated SKU processing with Glue/Step Function

Integration Layer

  • Headless CMS support (Contentful, Strapi)
  • REST API + Webhooks for real-time SKU updates
  • Multilingual QA testing module with human fallback

Quantified Impact

Content Turnaround Time
Before AI

4 weeks

After AI

<48 hours

Conversion Rate (Intl. Markets)
Before AI

4.2%

After AI

6.8%

SEO Organic Impressions
Before AI

1.3M/month

After AI

1.78M/month

Manual QA Requirement
Before AI

100%

After AI

12%

SKU Coverage Multilingual
Before AI

35%

After AI

100%

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