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Nike

Summary

Amia.ai implemented a Generative AI product-tagging system using a RAG architecture. This improved tagging accuracy while reducing the need for manual checks, integrating seamlessly with Nike’s existing product workflows.

Conservative Savings

$600K annually.

through improved operational efficiency.

Technical Approach

Generative AI (RAG)

Combined large language models with Nike’s internal product databases.

Confidence Scoring

Used NLP thresholds to filter out uncertain tags.

Additional Sales Insights

  • Scalable method suited for large, continuously updated retail catalogs.

  • Real-time dashboards track tagging precision and validate ROI.

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