Last updated: 2026-04-25

Bulk uploading documents

The fastest way to get a backlog of leases, invoices, BER certs and receipts into Anchorlet is the bulk uploader.

How to upload

  1. Open Documents in the top nav.
  2. Click Bulk upload (top right).
  3. Drag a folder of files into the dropzone, or click to pick. Up to 50 files per batch.
  4. The uploader runs each file through:
    • Dedupe — if the exact same file (matching SHA-256) is already in your workspace, the row is marked Duplicate and skipped.
    • Storage upload — file lands in Supabase Storage, scoped to your workspace path.
    • Text extract + classify — for PDFs with a text layer, Anchorlet pulls the text and runs the Haiku classifier. For images (JPEG/PNG/WebP), Claude reads the image directly.
    • Property match — looks at the filename + extracted text and tries to link the document to a property in your workspace.
  5. Files appear in the table with their classification result + matched property.

What you can upload

FormatPathNotes
PDFtext-layer or scanned (vision)Text-layer PDFs go through the cheap classifier; scanned PDFs fall back to vision.
JPEG / PNG / WebP / GIFimage classifierPhone photos of receipts, signs, etc. work.
XLSX / XLS / CSVspreadsheet pathRent statements, expense ledgers.

HEIC / HEIF aren't supported directly — convert first, or upload via the property page (which handles conversion downstream).

Per-property uploads

If you only have a single document for a specific property, use the Documents → Upload button on the property's detail page instead. Same pipeline, but the property is pre-linked so no fuzzy matching is needed.

Where things land

  • Successfully classified files go into the property's documents tab.
  • Files where the classifier was unsure end up in Documents → Needs review with a reason chip (e.g. "type uncertain", "no property match").
  • Files where the classifier hard-failed (corrupt PDF, no text layer, network error) stay in the queue with a "Try again" button.

See What the classifier does for the details on which document types Anchorlet recognises.