In this article, we will explore exactly what PDF invoice data extraction is and some of its benefits. We also share our simple 9-step process for extracting data from PDF invoices. Read on to learn more.
PDF invoice data extraction is the process of identifying and extracting key information from invoices in PDF format, such as invoice numbers, dates, and totals. It helps automate data entry tasks, saving time and reducing errors in financial workflows.
Example: BrightEdge Solutions extracts details from a PDF invoice, such as "Invoice #98765" and items like "Product X100 Widget." This information is then uploaded into their accounting software for accurate record-keeping.
Here are some of the most common benefits of using PDF extraction for invoices:
PDF invoice data extraction eliminates the need for manual data entry by processing large volumes of invoices quickly. This saves time and allows employees to focus on higher-value tasks.
Automation minimizes the risk of human error, providing consistent and reliable data. Accurate financial records help prevent costly mistakes and ensure compliance.
Extracted data integrates seamlessly into accounting, ERP, and inventory systems. This creates a smoother workflow from invoice processing to financial reporting.
Reducing manual intervention saves on labor costs while speeding up invoice processing. Timely payments also avoid penalties and improve cash flow management.
Automated systems can handle increasing volumes of invoices as your business grows. This ensures consistent performance without needing additional resources.
Securely archived invoice data simplifies audits and compliance reporting. Organized records make it easier to meet regulatory requirements.
Advanced tools adjust to various invoice designs and custom fields. This flexibility supports diverse industries and unique business workflows.
Use our 9-step PDF invoice extraction framework to efficiently handle your invoice data. Simply follow the steps below.
Start by uploading the PDF (Portable Document Format) invoice into the extraction tool. This can be done manually through a user interface or automatically using batch processing features for multiple invoices.
Example: A small wholesale business uploads "Invoice_12345.pdf" listing "Product A100 Widget" and "Product B200 Gadget" into their invoice management software for data extraction.
The tool analyzes the PDF to recognize its structure, including tables, images, and text fields. Preprocessing ensures that all relevant data can be accurately identified for extraction.
Example: The software processes a table with "20 units of Product A100 at $15 each" and "10 units of Product B200 at $25 each," identifying it as the main section for extraction.
The tool uses predefined templates or AI to locate critical fields like invoice number, dates, vendor name, and total amounts within the PDF. This step defines the data to extract.
Example: The software identifies "Invoice #56789," "Supplier: XYZ Corp," and "Total: $650" as key information to extract from a single-page PDF invoice.
Key data is extracted from the PDF, converting unstructured information into structured text or tabular data for further processing.
Example: The system extracts line items like "Product A100 Widget," "Quantity: 20," and "Subtotal: $300," saving them into a table for use in financial records.
Validation checks ensure that all extracted data matches the original values in the PDF. Any discrepancies, such as missing fields or incorrect totals, are flagged for review.
Example: The system validates the sum of line items against the "Total: $650" in the invoice and flags the file for review if there’s a mismatch.
The structured data is exported to a compatible format such as Comma-Separated Values (CSV) or directly integrated into accounting or Enterprise Resource Planning (ERP) software. This makes it ready for downstream workflows.
Example: The invoice data is exported to a CSV file containing fields like "Invoice #56789," "Total: $650," and itemized product details for import into an ERP system.
Exported data is used to automate tasks such as updating accounts payable, tracking inventory, or generating financial reports, reducing manual effort.
Example: The extracted data updates the accounts payable system, reducing the balance for "Supplier XYZ Corp" by $650 while updating stock levels for "Product A100 Widget."
When the tool encounters anomalies, such as missing fields or misidentified data, it flags these exceptions for manual review. This ensures accuracy in the final output.
Example: An invoice where the "Subtotal" field is missing is flagged for manual input of "Subtotal: $300" before the system processes it further.
The original Portable Document Format (PDF) and its extracted data are archived securely for future reference. This step supports legal compliance and audit readiness.
Example: The system saves "Invoice_12345.pdf" along with its extracted data in a cloud-based archive for easy retrieval during a financial audit.
BrightCore Solutions, a growing logistics company, is facing challenges with managing an increasing number of supplier invoices. Here’s how the team implemented our simple PDF invoice data extraction process. Simply follow the steps below.
Supplier invoices in PDF format are uploaded into the extraction tool, including those for freight hauling and equipment rentals. "Invoice_67890.pdf" includes freight charges of $2,000 and pallet rentals of $300.
The tool scans each PDF to detect tables, headers, and line items for accurate data extraction. A table with "Freight Charges: $2,000" and "Fuel Surcharge: $150" is identified during this step.
Key fields such as invoice numbers, vendor names, and totals are detected using templates or AI. The system captures "Invoice #67890," "Vendor: Transport Plus," and "Total Amount: $2,450."
Line items and payment details are converted into a structured format. One invoice records "Freight Charges: $2,000," "Fuel Surcharge: $150," and "Tax: $300."
Validation ensures that extracted data matches the original invoice. "$2,000 + $150 + $300" is confirmed to equal the total of "$2,450."
Validated data is exported into the accounting system, eliminating manual entry. Structured data for "Invoice #67890" is seamlessly added to accounts payable.
The extracted data automates expense reports and inventory updates. For example, freight costs of $50,000 are reported, and stock levels are updated for rented pallets.
Invoices and extracted data are securely stored for audits and compliance. "Invoice_67890.pdf" and related data are archived in the cloud for easy access.
Errors flagged during validation are reviewed and corrected. The tool is updated to recognize a "Shipping Discount" field after missing it on earlier invoices.
We hope you now have a better understanding of how invoice data extraction on PDFs works and how to use our 9-step PDF data extraction for invoices. If you enjoyed this article, you might also like our use-case on AI text recognition on PDFs.