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Ecommerce / Luxury-adjacent retail

Governed AI enrichment for product content at scale

Digital Commerce Architect

Designed a human-in-the-loop GenAI enrichment pipeline grounded in PIM — faster content readiness without sacrificing brand voice or governance.

AIPIMEnrichmentArchitecture

Challenge

A large catalog needed richer, on-brand descriptions and attributes across markets, but manual enrichment could not keep pace. Uncontrolled generative AI risked tone drift, inaccurate claims, and compliance issues.

Approach

  • Designed a human-in-the-loop enrichment pipeline with PIM as the source of truth.
  • Used LLMs for draft attribute fill, description variants, and localization assist — with brand and style guardrails.
  • Added quality scoring, audit logging, and editor review before publish.
  • Integrated via event-driven and API workflows so AI outputs landed back in governed product records, not one-off exports.

Outcome

Outcomes reflect approximate results in line with industry benchmarks for similar performance and commerce architecture programs — not audited client KPIs.

  • ~50–70% reduction in manual enrichment effort per SKU for targeted attribute sets
  • ~2–3× faster content readiness for new assortments
  • Quality gates: drafts rejected or edited before publish rather than silent auto-publish
  • Reusable pattern across categories without abandoning PIM governance

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