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Use case

Automate data entry

Automate data entry — pull the fields from emails, PDFs, and forms straight into your spreadsheet or CRM.

Start freeHow approvals work

You ask

“Pull the details from these order emails and add a row to my tracker for each one.”

What the worker does

  1. 1

    Monitor inbound emails, PDFs, attachments, and form submissions for the data you need.

  2. 2

    Extract the fields that matter — names, amounts, dates, line items, contact info.

  3. 3

    Match and add each extracted row to your spreadsheet, Airtable base, or CRM.

  4. 4

    Flag incomplete or ambiguous rows for manual review—approve the rest in bulk.

Result: Read 22 emails, added 22 rows, flagged 2 with missing fields.

Hand off automate data entry

Delegate it once and a worker handles it from here — you keep approval.

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Questions

Can AI automate data entry?
Yes. An AI worker reads emails, PDFs, and form submissions, extracts the fields you care about (names, amounts, dates, invoice numbers), and files them into your spreadsheet, Airtable, or CRM. The repetitive copy-paste work happens automatically, with every write waiting for your approval.
What kinds of data can it extract?
Any structured field from emails, attachments, and form submissions: customer names, addresses, order amounts, invoice numbers, line items, dates, phone numbers, company names. You define which fields matter for each task.
Where can the data be written?
Google Sheets, Airtable, HubSpot, Salesforce, Pipedrive, or any CRM you connect. The worker adds new rows or updates existing ones based on your rules—with a full audit trail of every change.
Will it write data without approval?
No. By default, every write is proposed and held for your approval—so a wrong extraction never lands in your database. You can bulk-approve good rows and manually review flagged ones.

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