It is not a search box but a retrieval API for programs: find pages similar in meaning, filter by date and other conditions, and pass the fetched text downstream as context. Useful for knowledge-base Q and A, material collection and automation. The cost is thinking clearly about what you want: loose filters return pages that look related but are useless, so keep a set of human-reviewed samples to judge results.
What it does
- Semantic retrieval that matches meaning, not keywords
- Filters for publish date, category and more
- Returns page text for downstream models
- Built for automation and batch calls
- API docs and examples make integration direct
Who it is for
- A self-built Q and A system needs a stable external context source
- Batch-finding similar pages for data cleanup
- Keyword search keeps missing differently worded but related results
- Running comparison tests on retrieval quality
How to get started
- Prepare twenty real queries as a small sample; do not start on production traffic
- Keep sources alongside fetched text for traceability
- Tighten filters based on false hits, then scale call volume gradually
