Essentials
Metadata
Add structured metadata to your documents for precise filtering and targeted queries, supercharging your search experience with file type, owner, upto 15 fields.
When you upload documents, you can attach structured metadata like file type, author, department, timestamp, tags, and more. This metadata becomes part of the index, allowing for precise filtering and targeted queries.
Note: For uploads, use the fields
When you upload documents, you can attach structured metadata like file type, author, department, timestamp, tags, and more. This metadata becomes part of the index, allowing for precise filtering and targeted queries. Benefit:
It supercharges your search experience. Instead of only relying on content, the AI can now use metadata to refine answers, disambiguate meanings, and improve precision. Use Case & Scenario:
You’re indexing thousands of company files. A user asks, “Which PDF did John upload in March about pricing?” The AI uses metadata like file type = PDF, uploader = John, and upload_date = March to find the right document instantly.
tenant_metadata and document_metadata (with the same schema as the original metadata field) to attach this information. These fields are not used in the QnA endpoint.
Adding Metadata
What it is:When you upload documents, you can attach structured metadata like file type, author, department, timestamp, tags, and more. This metadata becomes part of the index, allowing for precise filtering and targeted queries. Benefit:
It supercharges your search experience. Instead of only relying on content, the AI can now use metadata to refine answers, disambiguate meanings, and improve precision. Use Case & Scenario:
You’re indexing thousands of company files. A user asks, “Which PDF did John upload in March about pricing?” The AI uses metadata like file type = PDF, uploader = John, and upload_date = March to find the right document instantly.