AI Delivery Note to Excel Converter — Extract Shipment & Receipt Data Without Per-Carrier Setup
A delivery note leaves with the shipment and returns with handwritten receiving data — receiver signatures, damage notes, quantity corrections. This tool reads both the printed shipment fields and the handwritten receipt annotations on the same page, at 5–10 seconds per document.
Up to 99% accuracy on printed delivery notes · Files not stored after processing · No templates required
What You Can Extract from a Delivery Note
Type the column names you need — the AI locates each value across the document by understanding what it means, not where it sits on the page. This includes the handwritten annotations that appear on returned delivery notes after the receiver fills them in.
Why a Delivery Note Is Harder to Extract Than a Standard Form
A delivery note is the only logistics document that travels — it leaves the warehouse printed, rides with the goods, and returns covered in handwritten receiving data. It is two documents on one page. Template-based extraction reads the printed layer and ignores the handwritten half.
Where Template-Based Extraction Misses the Mark
Three distinct reference numbers coexist on one page. A delivery note typically carries its own delivery note number, a purchase order reference, and a carrier tracking or consignment number — often all three printed within the same header block. Fixed-position OCR cannot reliably distinguish which number belongs to which field because it reads text by coordinate, not by meaning.
The document comes back with handwritten annotations on top of printed fields. The receiver writes in quantities actually received, circles damaged items, scrawls "short shipped 2 boxes" in the margin, and signs the bottom. Template tools read this as one undifferentiated text stream, mixing the printed shipment data with handwritten corrections — or worse, ignoring the handwritten layer entirely because it does not match the template's expected text block.
Every supplier and carrier has a different layout. A direct-from-manufacturer delivery note and a common-carrier proof of delivery (POD) form share almost no visual similarity — yet they carry the same operational information. Template-based OCR requires a new parser definition for each format. Users on logistics forums consistently describe the reconciliation step as the bottleneck: matching differently formatted delivery documents against each other and against POs.
How Column-Name Extraction Reads Both Layers
Semantic understanding distinguishes reference numbers by meaning, not position. When you define columns like Delivery Note Number | PO Reference | Carrier Tracking Number, the AI reads the labels and context around each number to determine which is which — even when all three sit in the same header area or when some suppliers label them differently ("DN#", "Docket No.", "Delivery Ref").
Printed shipment data and handwritten receiving data are both extracted to the same spreadsheet. Add columns like Qty Shipped | Qty Received | Damage Notes | Receiver Signature. The AI reads the printed quantity from the supplier's table AND the handwritten correction from the receiver's annotation — outputting both into separate columns so you can compare shipped versus received on every line.
One column setup works across every supplier and carrier. Because the AI finds fields by understanding what each column name means — rather than matching a fixed pixel layout — you can upload delivery notes from 20 different suppliers and carriers in a single batch with one set of column definitions. The output is one unified Excel file, one row per delivery note, regardless of format differences.
From Stack of Delivery Dockets to Receiving Spreadsheet
If your team processes incoming shipments from multiple suppliers and needs both the shipment data and the receiver's confirmation in one structured spreadsheet, here is what the workflow looks like end to end.
Upload delivery notes and PODs
Drop in a batch of delivery note PDFs, scanned paper dockets from the dock, or photos of signed proof-of-delivery forms — from any carrier. Digital PDFs from supplier portals and scanned paper copies can be mixed in the same upload. For teams collecting delivery notes from suppliers or drivers, the Collection Link feature generates a shareable upload page so external parties submit documents directly to your processing queue without creating accounts.
Define the columns you need
Enter field names that span both shipment and receipt stages — Delivery Note Number | PO Reference | Supplier | Carrier | SKU | Qty Shipped | Qty Received | Damage Notes | Receiver Signature. For finance reconciliation, add Invoice Reference | Total Value. You can also define computed columns like Qty Discrepancy (Qty Shipped - Qty Received) and the AI calculates the difference during extraction — flagging mismatches before the data reaches your WMS or AP system.
Download the structured output
Export to XLSX, CSV, or JSON. Each delivery note becomes one row in the output table — with both shipment-origin fields and receiver-confirmation fields in adjacent columns. The output is ready for WMS goods receipt posting, PO reconciliation, carrier performance tracking, or three-way matching against supplier invoices. Google Sheets users can use the sidebar add-on to extract results directly into an active sheet. Processing runs at 5–10 seconds per page.
When It Works Best — and When to Spot-Check
Accuracy is high for standard delivery notes. A few specific conditions affect results — worth knowing before processing a large batch of returned documents.
When it works best
Digital PDF delivery notes from supplier or carrier portals. Machine-generated delivery notes from any system produce near-perfect extraction accuracy for header fields and line-item tables, including multi-page documents.
Scanned paper delivery notes at standard office quality. Clean scans at 300 dpi or higher extract reliably, including printed line-item tables. Legible handwritten annotations — receiver signatures, quantity corrections, damage notes — are read as structured data alongside the printed fields.
Mixed-supplier batches with one column setup. Delivery notes from different suppliers, carriers, and 3PL providers can be uploaded together and processed with the same column definitions. The output is one unified spreadsheet — one row per delivery note, regardless of format diversity.
Worth a spot-check
3rd or 4th generation carbon copies. Delivery notes and PODs are often carbon-copy forms — the top copy stays with the buyer, the second goes to the driver, and subsequent sheets degrade progressively. Later-generation carbons have faded text that reduces character recognition. Whenever possible, scan the first or second copy for best results.
Thermal paper receipts used as delivery notes. Some courier services use thermal paper for their POD forms. Aged thermal paper fades or darkens over time, creating uneven contrast. Documents printed more than 6–12 months ago on thermal paper may need a quick review of extracted values.
Heavy cursive or fast scribble in exception notes. Standard block handwriting and printed annotations extract reliably. Extremely rushed cursive — common in driver notes scribbled at the dock — may require manual verification. Structured mark fields like signature presence detection (signed / not signed) are more tolerant than full-text transcription of heavily cursive annotations.
Frequently Asked Questions
Can the AI distinguish between the Delivery Note Number and the Purchase Order Number when both appear on the same document?
Yes. The AI reads field labels and understands their semantic context. When you define a column named Delivery Note Number, it searches for the delivery docket's own identifier — not just any reference number in the header. It distinguishes that from PO Reference (the buyer's order number) and Carrier Tracking Number — even when all three reference numbers appear within a few lines of each other. This means your spreadsheet has the correct identifier in each column, which is essential for downstream PO matching and carrier reconciliation.
How does the tool handle handwritten receiver notes — damage descriptions, shortage comments, or signature confirmation — on a returned delivery note?
The tool treats handwritten annotations as extractable data rather than background noise. Add a column named Condition / Exception Notes and the AI reads handwritten comments about damaged items, shortage counts, or delivery issues written in the margins. Add a column named Receiver Signature (with format hint "Y/N" or "Present/Absent") and the AI detects whether a receiver's signature is present on the document. This is particularly useful for POD workflows where confirming receipt is the primary goal — rather than checking every document manually, you filter your spreadsheet for rows where Signature = No and follow up only on those.
Will faded carbon copies or thermal paper delivery notes extract accurately?
First and second generation carbon copies at standard scan quality extract reliably. Third and fourth generation copies — where ink pressure has diminished significantly — will have lower accuracy on fine-print fields like reference numbers and quantities. The AI still attempts extraction on these fields but may flag low-confidence values for review. Thermal paper (common in courier PODs) works well when the document is relatively fresh; thermal prints older than 6–12 months can darken or fade unevenly, which reduces extraction reliability. For archival thermal documents, a spot-check of the output is recommended before trusting the data downstream.
Can I process delivery notes from 20 different suppliers or carriers in one batch without creating individual templates?
Yes. Column-name extraction means you define your fields once — Delivery Note Number | PO Reference | Supplier | SKU | Qty Shipped | Carrier — and the AI finds each value across every document by understanding what each column name means, not by matching a fixed layout. Upload delivery notes from 20 different suppliers in a single batch, same column setup, one unified Excel output with one row per document. A manufacturer's multi-page delivery note and a courier's one-page POD form produce the same structured output from the same column definitions.
Can the extracted delivery note data be used for three-way matching with purchase orders and supplier invoices?
The structured output from your delivery note extraction provides the "goods received" data for three-way matching — the delivery note, the PO, and the invoice. However, the matching itself (comparing extracted delivery note data against your PO records and invoice data) happens in your ERP, AP system, or spreadsheet — the tool extracts the structured data, but it does not access your purchase order database or supplier invoice records to perform the match. What the tool enables is clean, consistent extraction of delivery note data so that the matching step — whether manual in Excel or automated in your ERP — runs on accurate inputs. For teams collecting delivery documents from field staff or suppliers, the Collection Link feature simplifies the document intake side: drivers and suppliers upload their delivery notes directly, and the processed output feeds into your reconciliation workflow.