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Use Extract from File when you want a workflow step to read structured or text data from a public file URL inside Fetch Hive.

Configuration

Add this step from the Utilities group in Search steps…. Supported formats: Tabular outputs are clamped to your plan iteration limit and a platform safety cap of 1,000 rows.

Output

Click Run in the step header to test the step. Fetch Hive shows the extracted result in Output after the run completes. Use the variable picker in a later step to insert the exact output path for your run. The base reference is:
For CSV or spreadsheet files, {{STEP_IDENTIFIER.output}} is the array of row objects (there is no .rows or .items wrapper). Pass it directly into an Iteration step:
Do not use {{extract_contacts.output.rows}} or {{extract_contacts.output.items}} — those paths resolve to null.

Field names

When First row is header is enabled, column headers are converted to variable-safe snake_case keys before they become row object properties: Duplicate sanitized keys get numeric suffixes (company_name, company_name_2). Inside the iteration body, reference fields from each row:

Example

Add Extract from File from the Utilities group. Set File URL to a public CSV such as https://example.com/contacts.csv. Keep File format on Auto-detect and leave First row is header enabled. Add an Iteration step with source {{extract_contacts.output}}. Inside the loop:
  1. Website Scrape on {{contacts_loop.item.website}}
  2. AI Prompt to write a unique outreach fact from the scrape result
After the loop, use Data Transform or Google Sheets to collect enriched rows.

Notes

  • Use a directly reachable file URL. This step fetches the file over HTTP; it does not upload files from your computer.
  • HTML extraction returns full-page text, not table rows.
  • PDF and DOCX extraction returns text suitable for downstream AI Prompt steps.
  • Breaking change: older workflows that referenced raw header strings with spaces (e.g. {{contacts_loop.item.Company name}}) must be updated to the snake_case keys after re-running the extract step.
See also: Data Transform, Creating and Editing, Testing and Iteration, and Error Handling