Transform PDF, scanned, and paper invoices into structured Excel files with vendor details, line items, totals, and tax amounts — automatically
Every accounts payable workflow begins with the same fundamental problem: invoice data arrives in a format that cannot be processed, analyzed, or imported without manual intervention. Vendors email PDF invoices. Suppliers mail paper invoices that get scanned into image files. Contractors send invoices from different invoicing platforms, each with its own layout, field labels, and page structure. The data on these invoices needs to be in a spreadsheet or accounting system before anything productive can happen with it, and the conversion from document to structured data is where most AP departments spend the majority of their processing labor.
The cost of manual invoice data entry goes beyond direct labor hours. Transcription errors in dollar amounts, transposed invoice numbers, and misread dates create downstream problems that consume additional time to identify and correct. A miskeyed invoice total that does not match the payment amount triggers an exception in the payment run. A wrong due date causes an early or late payment that affects cash flow planning or vendor relationships. These errors compound across hundreds or thousands of invoices per month, making manual conversion not just slow but systematically unreliable.
Lido converts invoice documents to Excel using AI that reads each invoice visually and extracts every field into structured spreadsheet columns. Upload invoices from any vendor, in any format, and get a clean Excel file with invoice numbers, dates, vendor details, line items, taxes, and totals organized in consistent columns. The AI handles format differences between vendors automatically, so adding a new vendor requires zero setup. Start with 50 free pages.
Header-level fields. The top portion of every invoice contains identifying information that the AI captures as individual Excel columns: invoice number, invoice date, due date, purchase order reference, payment terms (Net 30, Net 60, 2/10 Net 30), vendor name, vendor address, vendor tax ID, bill-to address, and ship-to address. These fields appear in different positions on different vendors' invoices. One vendor places the invoice number in a header table, another prints it in the upper right corner, and a third embeds it in a reference block. The AI identifies each field by its label and context, not by position, which is why it works across all vendor formats without templates.
Line item details. The line item table is the most data-rich section of an invoice and the most time-consuming to enter manually. The AI captures every row in the table with its constituent fields: item description or service description, item code or SKU, quantity, unit of measure, unit price, discount percentage or amount, tax per line, and extended amount. For invoices with simple single-column descriptions, each line item maps to one row in the Excel output. For invoices with multi-line descriptions that include part numbers, specifications, or delivery references within the description text, the AI captures the full description while still parsing out the numeric fields correctly.
Totals and financial summary. Below the line items, invoices summarize the financial details: subtotal before tax, tax amounts (sometimes broken into multiple tax lines for multi-jurisdiction billing), shipping or freight charges, handling fees, early payment discounts, credits or adjustments, and the grand total. The AI extracts each of these summary lines as separate fields in the Excel output, enabling downstream systems to validate the math and apply the appropriate accounting treatment to each component. International invoices may include currency conversion information, original currency amounts, and exchange rates, all of which are captured when present.
Many invoices include remittance instructions with bank details for wire transfer, ACH payment information, or payment portal URLs. The AI captures remittance information as additional fields in the output, enabling AP teams to verify payment routing without switching between the Excel data and the original invoice document. For invoices that reference previous payments or outstanding balances, the aging information and balance forward amounts are also extracted, giving a complete picture of the vendor relationship status from a single invoice.
The conversion process treats each invoice as a visual document rather than a text file. This distinction matters because many invoice PDFs, especially scanned ones, contain embedded images rather than selectable text. The AI performs visual analysis on the entire page, identifying text blocks, table structures, logos, and spatial relationships between elements. It determines which text block is the vendor name (typically near the logo at the top), which is the invoice number (near a label containing "Invoice" or "#"), and where the line item table begins and ends.
For scanned invoices, the process includes OCR that is specifically tuned for financial document content. Dollar amounts, dates, and numerical sequences receive enhanced recognition accuracy because the AI understands the expected formats for these fields. A string that appears near a "Total" label is expected to be a currency amount, so ambiguous characters are resolved in favor of digits and decimal points. A string near "Date" is expected to follow date format conventions. This context-aware OCR produces significantly higher accuracy on financial documents than generic OCR applied uniformly to all text on the page.
The output Excel file is structured for immediate usability. Each invoice occupies one or more rows depending on whether you need header-level output (one row per invoice with totals) or line-level output (one row per line item with header fields repeated). Column headers use standardized names that align with common accounting system import formats. Dates are formatted as Excel date values, not text strings, enabling sorting and filtering. Currency amounts are formatted as numbers with appropriate decimal places, enabling SUM formulas and pivot table analysis without reformatting. For organizations also converting form documents or contracts to Excel, the same AI handles all document types with consistent output quality.
Real-world invoice conversion encounters edge cases that generic document converters miss. Credit memos and debit notes follow invoice-like layouts but represent adjustments rather than new charges. The AI identifies these document types and flags them appropriately in the output so they are not confused with standard invoices during processing. Pro forma invoices, which are estimates rather than billing documents, are similarly identified. Duplicate invoices submitted multiple times by the same vendor are detected based on matching invoice numbers and amounts, with duplicates flagged to prevent double payment.
Accounts payable processing. AP teams receive invoices from dozens or hundreds of vendors each month. Converting the entire batch to Excel produces a single spreadsheet that serves as the invoice register for the period. AP clerks can sort by due date to prioritize payments, filter by vendor to consolidate payments, and cross-reference against purchase orders and receiving reports for three-way matching. The structured Excel data imports directly into accounting systems like QuickBooks, Sage, or SAP for payment processing, eliminating the manual entry step that typically consumes 60 to 70 percent of AP processing time.
Spend analysis and procurement intelligence. Converting historical invoice archives to Excel enables retrospective spend analysis that would be impossible when invoices exist only as PDFs. Extract a year's worth of invoices and suddenly you have a dataset showing exactly how much was spent with each vendor, in each category, at each location. This visibility reveals opportunities for volume consolidation, contract renegotiation, and maverick spend identification. Procurement teams use this data to prepare for RFP processes, benchmark pricing against market rates, and build business cases for strategic sourcing initiatives.
Audit preparation and compliance. Internal and external auditors need to examine invoice documentation as part of accounts payable and procurement audits. Converting invoices to Excel creates an auditable dataset where auditors can test transaction populations, stratify by dollar amount, and identify statistical outliers without manually reviewing individual invoice documents. The structured data supports automated audit procedures like Benford's Law analysis on invoice amounts, duplicate payment detection, and vendor master file validation against invoice data.
Freelancer and contractor payment tracking. Small businesses and finance teams managing payments to freelancers and contractors receive invoices in every imaginable format: Google Docs exports, Word documents saved as PDF, online invoicing platform outputs, and even photographs of handwritten invoices. Converting this mixed collection to Excel produces a unified payment tracking spreadsheet with contractor names, invoice dates, amounts, service descriptions, and payment status that replaces the scattered folder of PDFs that most organizations use as their contractor payment record.
Upload invoices from any vendor or format and get a structured spreadsheet with every field captured accurately
Upload your invoice PDFs to an AI-powered document converter that reads each invoice visually and extracts all fields into Excel columns automatically. The AI identifies invoice numbers, dates, vendor names, line item descriptions, quantities, unit prices, taxes, and totals regardless of the invoice layout. You get a downloadable Excel file with structured data in seconds, eliminating the hours of manual retyping that AP teams typically spend per invoice batch.
Yes. Upload invoices from any combination of vendors and the AI normalizes the extracted data into a consistent column structure. Whether you have QuickBooks invoices, SAP-generated PDFs, and freelancer invoices in the same batch, every invoice maps to the same Excel columns: invoice number, date, vendor, line items, and totals. This produces a single consolidated spreadsheet that is immediately usable for AP processing, spend analysis, and accounting system import.
Yes. The AI extracts each line item individually with its description, quantity, unit of measure, unit price, and extended amount preserved as separate cells in the Excel output. Multi-page invoices with line items spanning multiple pages are stitched together correctly. The output includes both header-level data like invoice number and vendor name and line-level detail, giving you the granularity needed for three-way matching, cost allocation, and general ledger coding.
The AI converts digital PDF invoices, scanned paper invoices, photographed invoices, and email invoice attachments. It handles invoices generated by any accounting or ERP system including QuickBooks, Xero, FreshBooks, SAP, Oracle, NetSuite, and custom invoicing software. The converter also processes handwritten invoices, invoices with stamps and annotations, and international invoices with non-English text and multi-currency amounts.
50 free pages. All features included. No credit card required.