ecommerce_ops · ecommerce · workflow
Delivery Hero QC automates product attribute extraction and title standardization with predefined agentic AI
Delivery Hero QC's manual processes for verifying and enriching product attributes across large, growing catalogs were time-consuming, costly, error-prone, and could not scale across numerous platforms and geographical regions.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Vendor title and image ingested
The first LLM receives the vendor product title and image as input.
Tools used
LLMsGPT-4oGPT-4o-mini
Outcome
Delivery Hero QC is successfully automating product attribute extraction and title standardization using LLM-powered AI agents, delivering improvements in efficiency, accuracy, data quality, and customer satisfaction, with significantly lowered operational costs and latency through knowledge distillation.
Results
VolumeEnsuring consistent and correct product information
Cost replacedsignificantly lowered operational costs and latency
Grounding & classification
Source type: technical build writeup
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agentic workflowcontent generationdata extractiondocument aiknowledge baseproduct catalogbuilder submittedhuman review describedproduction runtime claimedtools describedworkflow describedecommerceaccuracy improvementcost reductioncustomer satisfactionemployee productivitytime savedtechnical build writeupdata entry opsecommerce opsdocument to recordextract classify routehuman review queue