ecommerce_ops · ecommerce · workflow
Handmade.com modernizes product image and description handling with Amazon Bedrock and Amazon OpenSearch Service
Handmade.com had over 60,000 catalog products with many listings containing basic descriptions insufficient for search and SEO performance. Manual processing consumed on average 10 hours per week and required a team of several people, while sellers expected go-live timelines of under an hour.
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 · Image and metadata ingestion
Product images and metadata are fetched from the Handmade.com product data repository and Elasticsearch index.
Tools used
Amazon BedrockAmazon OpenSearch ServiceAnthropic's Claude 3.7 SonnetAmazon Titan Text Embeddings V2Amazon API Gateway
Outcome
Handmade.com successfully modernized its content generation workflow, streamlining seller interactions and enabling consistent content quality across a large and growing catalog, with vector-based search improving product discoverability and reducing friction in seller content workflows.
Results
Time saved10 hours per week
Volumeover 60,000 products
Grounding & classification
Source type: technical build writeup
27 fields verified against source quotes.
computer visioncontent generationknowledge searchragknowledge baseproduct catalogmetric backednamed customerproduction runtime claimedtools describedworkflow describedecommerceemployee productivitytime savedtechnical build writeupecommerce opsmarketing opsdocument to recordrag answering