Documents & search

A document is the unit Nordvec searches over: a file, a page, a message, an email, whatever you ingest. Once a document is processed it becomes searchable and can be cited in an answer.

Documents enter your workspace three ways:

• Connectors sync from a source you own (the connector owner). New and changed documents are picked up automatically. See the connector catalogue.
• Uploads of files you add in the app.
• Push sends a document to Nordvec directly from your own system. See Push documents.

Whichever way it arrives, Nordvec processes the document, splits it into passages, and indexes it for retrieval. Your documents are stored and searched in the EU.

A document has a status: processing while it is being indexed, indexed once every processing step has finished, and failed when it could not be processed.

A document from a connector is private to the person who connected it until that person shares it. An API key belongs to the workspace, so it sees what the workspace shares and never a person's unshared documents.

/documents/search is full-text search over the title and the whole text of every document you can see, however long the document is. Words match in the form you write them, in any language, and accents are ignored on both sides, so cafe finds café. There is no stemming: invoice does not match invoices.

Search runs standalone, without conversation context. It returns ranked documents, each with a snippet from its best-matching passage and a relevance score from 0 up to, but never reaching, 1.

curl https://nordvec.com/api/v1/documents/search \
  -H "Authorization: Bearer $NORDVEC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "query": "renewal terms", "limit": 10 }'

You can also list documents (/documents/list) or fetch one by id (/documents/{id}). See the API reference for the full set of parameters and response shapes.

Try itCopy link to this heading

Run a query against a small demo corpus. This searches six sample documents in your browser, ranked and sourced, the same shape a real search returns.

Semantic retrieval, which matches passages by meaning rather than exact words, is what powers a conversation's cited answers. The search endpoint itself matches words.

A document can carry a knowledge type in content_type (for example decision, runbook, policy or faq). A pushed document sets it with the push API's type; a document with no type has content_type: null. Search and list both filter on it with contentType.

Search gives you passages to work with directly. When you want a written answer instead of raw passages, a conversation retrieves over the same documents and cites them in its reply.