Logistics documents

How do I extract delivery dates from proof of delivery documents?

Direct answer for teams evaluating document automation workflows.

Short answer

Lido helps teams extract delivery dates from proof of delivery documents by combining AI extraction, review, validation, and clean exports to operations spreadsheets or shipment workflows.

Direct answer

Delivery dates on PODs should be extracted from date fields, signature blocks, timestamps, or driver-upload metadata and reviewed when handwriting or scans are unclear. Lido helps make those dates structured and exportable.

For “How do I extract delivery dates from proof of delivery documents?”, define the exact fields, rows, review rules, and destination before scaling automation across a larger document batch.

What the workflow should include

The workflow should validate delivery date, order number, signature, carrier, consignee, and source-file context before sending data to operations.

For “How do I extract delivery dates from proof of delivery documents?”, pay special attention to driver uploads, inconsistent scans, abbreviations, handwriting, missing signatures, and mixed logistics document types; those edge cases usually determine whether the output is usable downstream.

Before scaling “How do I extract delivery dates from proof of delivery documents?”, test a small set of real files and compare the extracted rows against the originals so the team can tune fields, review rules, and exports before higher-volume automation begins.

How Lido helps

For teams trying to extract delivery dates from proof of delivery documents, Lido combines AI document extraction with spreadsheet-style review, validation, and automation for logistics and operations teams.

That lets teams answer “How do I extract delivery dates from proof of delivery documents?” with a reusable process that can be tested, corrected, and connected to operations spreadsheets, shipment trackers, TMS exports, or exception queues.

Example workflow

  1. Collect logistics documents from email, shared folders, uploads, or another intake path.
  2. Define the target fields or table columns: delivery dates, recipient names, order numbers, signatures, and exceptions.
  3. Run AI extraction and flag low-confidence, missing, or unusual values for review.
  4. Export approved results to a spreadsheet or operations workflow and monitor exceptions over time.

Built for real document workflows

Need to turn messy documents into clean spreadsheet-ready data?

Lido helps teams extract, review, and automate data from PDFs, forms, invoices, statements, and other recurring document workflows.

Talk to Lido