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Classify

What this page is — the capability that reads a document and places it in your Papers taxonomy: its family, the best-matching type from your own catalog, filing tags, and the folder it belongs in.

What it is for — so an imported or badly-named file gets filed where a person would have filed it, and a backlog of untitled PDFs stops being a manual sorting job.

The problem it solves — imported files pile up untitled and unfiled, and are never found again by the people who need them.

Route: /org/papers/documents/<document>/ai → Understand → Classify · Permission: Use AI drafting/extraction/Q&A for documents. · Utility: papers_auto_classify · Cost: 450 credits estimated, 1,800 maximum.


1. What it is​

Classify makes four judgements at once, and the important thing about all four is where the answers come from:

OutputChosen from
FamilyA fixed list of seven — see §5
TypeYour organisation's own document-type catalog
FolderYour repository's existing folder paths
TagsFreely generated from the content, lowercase, 3–8 of them
It suggests from your catalog — it never invents

The type code and folder path come only from types and folders that already exist in your organisation. When nothing fits, it returns an empty value rather than making one up.

So a document that keeps coming back with no type is not a failure of the classifier. It is the classifier telling you your catalog has a gap. Add the type or the folder, then re-run.

It judges by substance, not by the title. A file called scan_0043.pdf containing a tax invoice classifies as a tax invoice. The current title is used only as a weak hint, and may be empty.


2. Why you would use it​

Filing is the work everyone defers. The cost shows up months later, when the repository has four thousand documents and no reliable way to find the one you need.

  • It makes an import tractable. A migration of legacy files is a sorting problem before it is anything else. Classification turns "3,000 PDFs in a folder" into "3,000 typed, tagged, filed documents to review".
  • Tags are the part humans never do. Three to eight tags per document, drawn from subject, counterparty, domain and jurisdiction, is precisely the metadata that makes search work and precisely what nobody types by hand.
  • confidence lets you triage. Classify a batch, accept everything above your threshold, and spend human attention only on what came back uncertain.
  • It audits your catalog. A steady stream of empty suggested_type_code is evidence that a type is missing — a finding you would not otherwise get.

3. What you provide​

Classify has two modes, and which one you are in is decided by where you run it.

ModeYou provideUse when
Document modeNothingYou have a Papers document open. It reads the body and title
Raw-text modeThe text, pastedYou are classifying an uploaded or legacy file whose content was extracted outside a Papers document

Raw-text mode is the one that makes this capability useful for migration — it does not require the content to be a Papers document yet. Paste what the extractor gave you:

TAX INVOICE No. INV-2231 Bill To: Gatiro Retail... GST 18%... Total INR 45,900

The classifier does not need the whole document. A first page carrying the header, the parties and the totals is usually enough.


4. What it reads automatically​

Uniquely among the AI capabilities, Classify reads your organisation's configuration as well as the document — it cannot suggest a type it has not been shown.

ReadFromUsed for
Document textThe open documentThe classification itself, in document mode
Current titleThe documentA weak hint only. May be empty
Available typesYour org catalog — code, name, familyThe menu suggested_type_code is chosen from
Available foldersYour repository folder pathsThe menu suggested_folder is chosen from

5. What you get back​

FieldTypeValuesMeans
familyenumtransactional, agreement, correspondence, certificate, policy, record, customExactly one. The broad class
suggested_type_codestringa code from your catalog, or emptyBest-matching type. Empty when none is a reasonable fit
confidencenumber0–1For family and type together, not separately
suggested_tags[]string[]3–8 entries, lowercase, no duplicatesFiling tags from subject, counterparty, domain, jurisdiction
suggested_folderstringan existing path, or emptyBest-fitting folder. Empty when none fits

confidence covers the family and type jointly. A high score does not tell you the folder is right — folder and tags carry no separate confidence, so review them on their own terms.


6. Worked example​

A finance administrator is clearing an imported batch and runs Classify on a scanned file whose only name is a scanner serial number.

Input (raw-text mode):

TAX INVOICE No. INV-2231 Bill To: Gatiro Retail Pvt Ltd... GST 18%... Total INR 45,900

Result:

family: transactional suggested_type_code: INV confidence: 0.94 suggested_tags: ["invoice", "gst", "gatiro", "fy2026"] suggested_folder: /Finance/Invoices/2026

What the administrator does with it. At 0.94 the family and type are accepted without review. The folder is checked — /Finance/Invoices/2026 exists and is right — and the four tags are kept as generated. Note fy2026: the classifier derived a fiscal-year tag from the invoice date, which is the kind of tag that makes a later search work and which nobody types manually on document 300 of a batch.

Had suggested_type_code come back empty, the finding would have been about the catalog rather than the document: no invoice type exists to file it against.


7. Running it​

  1. Open a document in Orbit Papers, or have the extracted text of a legacy file ready.
  2. Open the AI Assistant drawer, or go to the document's AI workspace.
  3. Choose Classify under Understand.
  4. In document mode there is nothing to type; in raw-text mode, paste the text.
  5. The family, type, tags and folder suggestion appear in the result tab.

The suggestions are not applied. Nothing about the document's type, folder or tags changes until a person accepts them. Classification is advice about filing, not filing.

Classify can be set to auto-run from the type's AI Config tab — though note the circularity: a document that already has a type does not usually need classifying. The useful case is the capture inbox, where documents arrive without one. See AI configuration.


8. The admin contract​

Must be trueWhereWhat happens if it is not
Your role holds Use AI drafting/extraction/Q&A for documents.Role editorThe AI Assistant button does not appear
The papers_auto_classify utility is activeOrbit AI Flow → utilities"This utility is currently disabled"
The utility is enabled for your organisation/org/ai-utilitiesAbsent from Understand, with no error
papers.ai_monthly_credit_cap not yet reachedSystem Config"monthly AI credit cap reached: n of n credits used this month"
Document types exist for the families you handleType designersuggested_type_code comes back empty. Not an error — there is nothing to suggest
Repository folders existRepositorysuggested_folder comes back empty for the same reason

This is the capability whose quality depends most directly on configuration elsewhere. A rich catalog gets specific suggestions; an empty catalog gets empty fields and a family label.

Confidential documents: automatic runs are blocked, manual runs are not

For a confidential document, auto-run is default-denied — a platform administrator must set papers.ai_confidential_cloud to the literal allow, and the block appears only in the server log. A manual press still works, and where a local model key is configured the run is forced on-prem and audited on the timeline as ai_local_routed.


9. Don't confuse this with…​

Type from documentCreates a new document type from a sample. Classify only picks from types that exist
Capture inboxWhere unfiled documents arrive. Classify is what tells you where they go
Smart fieldsExtracts values from within a document. Classify decides what the document is
Zonal extractionReads fixed positions on a page. Classify reads meaning

10. Troubleshooting​

SymptomCause
suggested_type_code is emptyNo type in your catalog is a reasonable fit. Add the type, then re-run (§1)
suggested_folder is emptyNo existing folder fits. It will not invent a path
The same wrong type keeps being suggestedYour catalog has no better option. The classifier picks the best available, not the right one
The document's type did not changeSuggestions are never applied automatically. A person accepts them (§7)
confidence is high but the folder is wrongconfidence covers family and type only — folder and tags carry none (§5)
Fewer than three tagsThe content is too thin to draw them from — common on a one-line letter
Raw-text mode is not offeredYou are in document mode. Raw text is for content that is not yet a Papers document (§3)
The capability is missing from UnderstandRole lacks Use AI drafting/extraction/Q&A for documents., or the utility is off for the organisation (§8). The document type does not gate it — AI Config controls auto-run only