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Lasso Enrich takes partial product records — as little as a product name or SKU — and fills in every missing field with sourced, cited data. Each value comes with a basis showing exactly where the information came from.

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How it works

  1. Pass in what you have — Provide one or more items with whatever data you already know (name, SKU, brand, etc.).
  2. Define the target schema — Tell Lasso what fields you want filled in (or use the default product schema).
  3. Lasso researches each product — The AI searches Lasso’s database, finds the product, and extracts structured data.
  4. Get back complete records — Every field is filled in with citations, reasoning, and confidence scores.

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The basis

Every enriched field includes a basis that tells you:
  • citations — The sources used (URL, title, excerpt)
  • reasoning — How the AI determined the value
  • confidence — high or low
This transparency is critical for product data quality. You can verify values, filter by confidence, or show sources to your users.

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Schema options

Same as Search — use schema_id, inline columns, or omit both for the default product schema.

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Sync vs async

  • Sync (default): For up to 5 items, Lasso processes and returns results in the same request.
  • Async: For larger batches (>5 items) or when you pass webhook_url, Lasso returns 202 immediately and delivers results via webhook.

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Example: Search then Enrich

A common pattern is to search for products first, then enrich the results with additional detail. 
// 1. Search for products
const search = await client.search({
  query: "best wireless mice for gaming 2025",
  columns: [
    { key: "name", label: "Name", type: "text" },
    { key: "brand", label: "Brand", type: "text" },
  ],
  max_results: 5,
});

// 2. Enrich with full detail
const enriched = await client.enrich({
  items: search.results.map(r => ({ data: r.data })),
  columns: [
    { key: "name", label: "Name", type: "text" },
    { key: "brand", label: "Brand", type: "text" },
    { key: "price", label: "Price", type: "number" },
    { key: "dpi", label: "Max DPI", type: "number" },
    { key: "weight", label: "Weight (g)", type: "number" },
    { key: "features", label: "Features", type: "tags" },
    { key: "description", label: "Description", type: "text" },
  ],
});

for (const item of enriched.items) {
  console.log(`${item.data.name} — ${item.data.price}g, ${item.data.dpi} DPI`);
}

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Credits

Credit cost depends on the thinking level you choose:
ThinkingModelCredits/itemBest for
hardGemini 3.1 Pro4Complex or ambiguous products
mediumGemini 3.1 Lite2General-purpose enrichment (default)
lowGemini 2.01Fast, straightforward lookups
By default, Lasso uses web search to research each product and provides a basis with citations for every enriched field. You can disable this with web_search: false — the AI will fill fields from its own knowledge without citations, which is faster and still accurate for well-known products.

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Next steps

  • Enrich API reference — Full parameter and response documentation.
  • Search — Discover products to enrich.
  • Glossary — Control terminology during enrichment with use_glossary: true.