exa-websets-search

Build structured data collections by creating a webset, running targeted searches to populate it, then enriching items with AI-extracted fields like URLs and metadata. The three-step workflow—Validate, Expand, Enrich—ensures search quality before scaling data collection and keeps enrichment costs efficient by batching extraction.

Yes. Automate webset population by running precise web searches or importing existing CSV data directly. This eliminates manual data entry and lets you combine multiple data sources into a single validated collection for market research or competitor analysis.

Start with count:1—run your search with a single result to confirm the query returns relevant items before expanding. This procedural validation step catches search criteria issues early and prevents wasted enrichment on poor-quality datasets.

Use AI-powered enrichments to add custom structured data fields—text, URLs, categorical options—across every item in your webset simultaneously. Batch enrichment defers extraction costs until you're confident in your collection, reducing processing overhead.

Yes. Export validated items and their enrichments as structured output compatible with RAG pipelines and downstream analytics workflows. This supports integration into larger data processing and retrieval systems without additional transformation.

Incremental expansion runs controlled searches with fixed queries and criteria to grow collections methodically with quality checks. Bulk import brings in existing CSV datasets directly. Use expansion for discovery-driven collection building and import for consolidating prepared data sources.