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Connect Paige to Google Sheets and Excel

Get Paige's extracted data into a spreadsheet: open the one-row-per-document CSV Paige exports, or have Zapier, Make, or Power Automate append a row to a Google Sheet or an Excel table for every document Paige finishes — with a link to the PDF.

For everyone20 minutesVerified 2026-09-05

Before you begin

  • A Google Sheet or an Excel workbook (in OneDrive or SharePoint) with a header row for the fields you want
  • For the automatic path, an account on Zapier, Make, or Power Automate that includes the SFTP connector, and an SFTP server Paige can reach
  • A Paige scan job with document types and fields set up

At the end of this guide, every value Paige extracts — vendor, invoice number, dates, totals, whatever your document types hold — is in a spreadsheet, either as a batch you open or as rows that appear on their own as documents finish.

A spreadsheet is the most common "system" of all, and often the fastest way to see whether Paige is reading your documents the way you want. Two routes.

Route 1 — Open the CSV Paige exports

Paige writes a one-row-per-document CSV with a column for each field, plus the PDF's file name and the document type. Get it two ways:

  • Download: in Paige, open Documents, click Export, and in the Export Documents dialog choose the Scope (a batch or all), the Filters (Reviewed only, Field Data with fields, Status not yet exported), tick Download under Destinations, and confirm. Paige emails a link when the download is ready; the zip contains the PDFs and the data files.
  • SFTP: if the scan job exports to SFTP (the FTP card under Settings > the scan job > Export), turn on Generate combined metadata file so every export run also writes the combined CSV to the folder.

Open the CSV in Google Sheets (File > Import) or Excel. What you should see: a header row and one row per document. Line-item tables aren't in this file; they're in each document's .json and .xml, and in the sectioned per-document .csv.

That's the batch route. It's enough for monthly reports and one-off audits.

Route 2 — A row per document, automatically

Have an automation append a row every time Paige finishes a document. The pattern is the standard one: SFTP trigger → keep only the data file → read the values → add a row.

First, point Paige at your SFTP server: Settings > the scan job > Export > the FTP card; enter FTP Address, Port 22, Username, Password, FTP Folder Path; Test Connection (FTP connection successful!); connect; then turn on Enable Auto Export with Auto Field Entry Complete = Yes, and Save. Allow Paige's address ranges through your firewall — Outbound IP ranges for firewall allow-lists.

Put the field names in the sheet's header row exactly as they're named in Paige, plus Document Type and PDF.

Google Sheets with Zapier

  1. SFTP by Zapier → New or Updated File, folder = the scan job's folder.

  2. Filter by Zapier: File Name (Text) Ends with .json.

  3. Code by Zapier → Run Javascript, file mapped to the trigger's file:

    const doc = await (await fetch(inputData.file)).json();
const out = { pdf_file: doc.metadata.pdf_file, document_type: doc.metadata.document_type };
for (const [k, v] of Object.entries(doc.fields)) out[k] = v;
return out;

  1. Google Sheets → Create Spreadsheet Row. Pick the spreadsheet and worksheet; Zapier lists the header names as fields — map each from the Code step. Put pdf_file in the PDF column (or, if the PDFs also go to a Google Drive folder via that guide, the file's link).

  2. Turn the Zap on.

Google Sheets with Make

  1. SFTP → Watch files in a folder; filter File name Ends with .json.

  2. SFTP → Get a file, then JSON → Parse JSON.

  3. Google Sheets → Add a Row, mapping the parsed fields to the columns.

Excel with Power Automate

The workbook must live in OneDrive for Business or SharePoint, and the data must be in a formatted table (select the header row and data, Insert > Table).

  1. SFTP - SSH: When a file is added or modified, folder = the scan job's folder, Include file content on.

  2. Condition: File name ends with .json.

  3. Parse JSON on the trigger's File content, schema from a real .json.

  4. Excel Online (Business) → Add a row into a table. Location, Document Library, File, Table; then one input per column, mapped from the parsed fields.

  5. Save.

Note

Power Automate's Excel connector locks the file briefly after each write and doesn't like other people editing at the same moment. Keep the automation's workbook as a landing table and link a second workbook to it for analysis.

Test it

Process one document through the scan job and wait for the export. What you should see: a new row with the document's values, within the automation's polling interval.

When it doesn't work

SymptomWhere to look
No row appearsWrong folder in the trigger, or the .json filter is missing (you'd see errors from parsing a PDF as JSON).
Columns don't line upHeader names must match what you map; a renamed header breaks the mapping.
Dates or amounts come in as textThey are text — Paige exports values as printed. Format the column, or convert in the automation.
Excel step fails with a lock errorSomeone had the workbook open. Use a landing workbook nobody edits.

If the Paige side is the problem, contact Ademero support with the scan job name and the message from Test Connection.