Case Study · Transform · GenAI on e-commerce

AI cuts product creation time by 80% for an e-commerce platform.

A PE-backed distribution group needed to scale catalogue operations without scaling the cost base. We orchestrated GenAI across the e-commerce stack and rebased the unit economics.

−80%
Product description creation time
−50%
Staffing cost reduction
PE-backed
Distribution group (anonymised)
99%
Project velocity uplift, AI Factory

The challenge

A PE-backed distribution group with a tens-of-thousands-SKU catalogue was running product description creation manually. Speed-to-market was constrained by the throughput of the copy team. The PE investor was pushing for top-line growth that the operating model could not deliver.

  • Tens of thousands of SKUs requiring tailored product descriptions across multiple channels.
  • Manual copy workflow throttling new product introduction.
  • Staffing cost growing faster than catalogue revenue.
  • PE investor pressure on both growth rate and operating margin.

Our approach

We deployed a bespoke GenAI capability across the e-commerce stack, orchestrated by agentic agents that handle the end-to-end product onboarding workflow: from supplier data ingestion, through copy generation, to channel-specific publication. Senior consultants ran the brand and quality gate.

The work covered both the AI build and the operating-model change around it. Copy team roles were re-cast as reviewers and brand stewards; the volume work shifted to agents.

What we delivered

An AI-led product onboarding engine running on the AI Factory operating model, with measured outcomes settled against the original investor case.

  • Product description creation time reduced by 80% across the catalogue.
  • Staffing cost in the copy team reduced by 50% while catalogue throughput increased.
  • Quality gate retained by senior brand reviewers, with measured improvement in published quality.
  • Continuous-improvement programme under the Extend pillar keeps the GenAI capability current with new channels and new categories.
Outcome

Top-line growth compounding. Operating cost line going the other way.

More AI-led work in production

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