Where should source documents and extracted results be stored in an automated workflow?

Direct answer

For teams asking “Where should source documents and extracted results be stored in an automated workflow?”, the strongest answer is a repeatable workflow with defined fields, review, validation, and downstream handoff. The goal is to turn email attachments, inbox-driven PDFs, Gmail files, Outlook attachments, and recurring document submissions into structured data the business can trust.

For “Where should source documents and extracted results be stored in an automated workflow?”, define the exact fields, rows, review rules, and destination before scaling automation across a larger document batch.

What the workflow should include

For teams trying to decide where source documents and extracted results should be stored in an automated workflow, a production-ready answer should capture sender, subject, attachment type, document type, extracted fields, review status, and destination columns while preserving a consistent schema from one document to the next.

For “Where should source documents and extracted results be stored in an automated workflow?”, pay special attention to irrelevant attachments, logos, wrong senders, duplicate emails, unsupported file types, and files that need classification first; those edge cases usually determine whether the output is usable downstream.

How Lido helps

For teams trying to decide where source documents and extracted results should be stored in an automated workflow, Lido combines AI document extraction with spreadsheet-style review, validation, and automation for operations teams processing document-heavy inboxes.

That lets teams answer “Where should source documents and extracted results be stored in an automated workflow?” with a reusable process that can be tested, corrected, and connected to Google Sheets, Excel, shared folders, review queues, or downstream systems.

Example workflow

1. Choose where new documents arrive: email, upload, shared folder, or application.
2. Separate raw files, processed files, exceptions, and approved exports.
3. Decide where reviewers will work and where final results will live.
4. Name, archive, or route files based on status and extracted values when needed.