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Configure Enrichment Job

Pick taxonomy, upload schema, then upload SKU file. The next step lets you map columns.

① Taxonomy Level
🏭
Level 1
Category-level
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Level 2
Sub-category
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Level 3
Full parametric
② Attribute Schema File
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Drop schema XLSX or click
Optional in demo
✓
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③ SKU File
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Drop SKU XLSX or click
Up to 50MB
✓
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✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ● Column mapping› Context check› Pre-scrape› Enrichment

Map your columns

Auto-detected from your file. Adjust mappings if needed.

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Your column
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Required fields not mapped:
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    ✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ✓ Column mapping› ✓ Context check› ✓ Pre-scrape› ● Model selection› Enrichment› Normalization› Generic attributes

    Choose enrichment model

    Select how attributes will be extracted from scraped product sources. Each path uses the context file you already generated.

    1
    Gemma 4 + Claude API fill-in Recommended
    2
    Claude API only
    3
    Gemini 2.5 Pro API
    ✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ✓ Column mapping› ✓ Context check› ● Pre-scrape› Model selection› Enrichment› Normalization› Generic attributes

    Pre-scrape review

    Scrape all sources, review the extracted text, then approve before enrichment.

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    Click "Scrape all sources" to begin.
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    Source
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    Edit the scraped text. This will be saved as your manual version — Gemma will use this instead of the original.
    Click "🌐 Browser view" tab to load
    Change the URL. Saving will re-scrape from the new URL.
    ✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ✓ Column mapping› ● Context check› Pre-scrape› Model selection› Enrichment› Normalization› Generic attributes

    Context check

    Before enrichment runs, every taxonomy in your SKU file must have a matching context file. Context files teach Gemma what each attribute means and how to extract it.

    Unique taxonomies
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    With context
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    Missing
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    Schema file: none uploaded — required for richer context
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    Context Library

    Per-taxonomy enrichment context files. Pre-built, manual upload, or generated via Claude.

    Loading library…
    Context file
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    Generate context via Claude

    Claude reads your attribute schema + sample SKUs and writes a custom MD context file.

    Claude will read up to 5 sample SKUs from this taxonomy in the current job, plus the attribute names, and generate a context file matching your template format.
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    ✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ✓ Column mapping› ✓ Context check› ✓ Pre-scrape› ✓ Model selection› ● Enrichment› Normalization› Generic attributes
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    ✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ✓ Column mapping› ✓ Context check› ✓ Pre-scrape› ✓ Model selection› ✓ Enrichment› ● Normalization› Generic attributes

    Normalization

    Loading normalization data…
    📝 Normalization Notes
    ✓ Taxonomy› ✓ Schema› ✓ SKU file uploaded› ✓ Column mapping› ✓ Context check› ✓ Pre-scrape› ✓ Model selection› ✓ Enrichment› ✓ Normalization› ● Generic attributes

    Generic Attributes

    AI finds additional attributes from scraped content not captured in enrichment. Columns: G_Attribute_Name_N, G_Attribute_Value_N, G_Attribute_UOM_N

    Click Find Generic Attributes to start. Uses on scraped content.
    ✦
    PartminerGemma 4
    Component intelligence · ask about parts, datasheets, compliance
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