Choose a PDF or image
Use a digital PDF, scanned PDF, phone photo, or exported image. Scans automatically use OCR in your selected language mode.
Free online invoice OCR
Invoice OCR for PDFs and images.Turn invoices into JSON.
Stop retyping invoices by hand. Upload a PDF, scan, or photo to extract invoice numbers, dates, suppliers, line items, tax, and totals into editable JSON.
PDF & image invoices19 language modesPrivate, in-browser
Upload your invoice
Files stay on your deviceDrag & drop an invoicePDF, JPG, PNG, WebP or BMP · Up to 25 MB / 50 PDF pages
Your invoice data
Your extracted data will appear here after you upload an invoice file.
One invoice. The details you need.
Get a structured invoice record with source text for every page. Missing values are left null, so you can review and complete them.
invoiceNumberinvoiceDatedueDatesuppliercustomerlineItems[]taxBreakdown[]totalspaymentrawTextFrom invoice to JSON in three steps
Check the details
Review dates, parties, quantities, prices, taxes, and totals. The parser recognizes common invoice labels across nine languages, and you can correct the JSON.
Use your data
Copy or download the JSON, including additional labeled fields and full page text, ready for your records or an import workflow.
Your invoice is processed on your device. OCR engine and selected language files download as needed. Password-protected PDFs must be unlocked first.
INVOICE DATA EXTRACTION
Extract invoice data without the copy-and-paste work
Invoices rarely arrive in one tidy format. Some are digital PDFs, others are scans, and plenty are quick phone photos. Toolroot reads all three, finds the useful details, and organizes them into a consistent JSON record you can review before using.
The result includes the original page text alongside detected fields. If a value is unclear or missing, it stays visible for review instead of being silently invented. That makes the tool useful for accounts payable checks, bookkeeping preparation, expense records, and data-entry workflows.
STRUCTURED OUTPUT
What can the invoice OCR extract?
Field detection adapts to common invoice layouts while preserving the raw source text for anything that needs a human check.
Invoice details
Invoice number, invoice date, due date, purchase order, payment terms, and currency.
Supplier and customer
Vendor, bill-to and ship-to details, email addresses, tax IDs, and available contact information.
Line items
Descriptions, item codes, quantities, unit prices, discounts, tax labels, and line totals.
Totals and payment
Subtotal, tax, shipping, discounts, amount paid, amount due, bank details, IBAN, and bank codes.
MULTILINGUAL PDF & IMAGE OCR
Built for digital invoices, scans, and photos
Upload a text-based PDF for fast extraction, or use OCR for a scanned PDF or invoice image. Supported image formats include JPG, PNG, WebP, and BMP. Multi-page PDFs can contain up to 50 pages.
Choose a single-language or mixed-language OCR mode for English, Spanish, French, German, Portuguese, Italian, Hindi, Arabic, Simplified Chinese, or Japanese. Mixed modes help when an invoice combines English headings with another language.
ACCURACY TIPS
Help the OCR read your invoice clearly
- Use a sharp scan or photo with even lighting.
- Keep the entire invoice visible and avoid steep camera angles.
- Select the language that matches the document text.
- Turn on full-page OCR when a PDF text layer is incomplete.
- Review dates, totals, and bank details before importing the JSON.
COMMON QUESTIONS
Invoice OCR FAQ
What is invoice OCR?
Invoice OCR uses optical character recognition to read text from an invoice PDF, scan, or photo. This tool then organizes recognized text into fields such as invoice number, supplier, dates, line items, tax, and total.
Can I extract data from a scanned PDF invoice?
Yes. If a PDF page does not contain readable embedded text, the tool renders that page and applies OCR automatically. You can also force OCR on every page.
Can I convert an invoice image to JSON?
Yes. Upload a JPG, PNG, WebP, or BMP invoice image. After OCR finishes, review the detected fields and copy or download the editable JSON.
Which invoice languages are supported?
The language menu includes English, Spanish, French, German, Portuguese, Italian, Hindi, Arabic, Simplified Chinese, and Japanese, plus mixed English modes for bilingual invoices.
Is this invoice OCR free and private?
Yes. No sign-up is required. Invoice processing runs locally in your browser, so Toolroot does not upload or retain the source file.
Will every invoice field be perfectly accurate?
No OCR system is perfect. Image quality, unusual layouts, handwriting, and faint text can affect results. Always compare important dates, totals, tax values, and payment details with the original invoice before using the data.
INVOICE OCR GUIDE
A Practical Guide to Invoice OCR and Accounts Payable Extraction
Learn how invoice and receipt OCR works, which fields can be extracted, where human review belongs, and how JSON or API output can fit into an accounts-payable workflow.
1. What invoice OCR does
Invoice OCR turns text trapped inside a PDF, scan, or photograph into machine-readable information. Optical character recognition handles the visible words, while invoice-specific parsing looks for business fields such as invoice number, issue date, due date, supplier, customer, purchase order, line items, tax, subtotal, and total. The result is more useful than plain extracted text because each detected value is placed in a predictable JSON structure for review.
OCR invoice recognition is not the same as accounting approval. A parser can suggest that a number is the total or that a line belongs to a product table, but it does not know whether the purchase was authorized, delivered, coded to the right account, or duplicated elsewhere. Treat extraction as the beginning of a workflow. Important values should be checked against the source document before they enter bookkeeping, payment, or reporting systems.
2. How the extraction process works
The browser tool first checks whether a PDF already contains readable text. Digital invoices often do, so their words and positions can be collected without running OCR. A scanned PDF or image has no dependable text layer; those pages are rendered and passed through OCR in the selected language. You can also force OCR on every PDF page when an embedded text layer is incomplete, scrambled, or visibly different from the document.
After text extraction, the invoice parser examines labels, positions, table headings, amounts, and common date patterns. It builds a structured record while preserving page text and source lines. Missing or uncertain fields remain null or produce review warnings instead of being silently invented. This design makes the output easier to audit because a reviewer can compare the proposed JSON with both the original invoice and the extracted text.
3. Digital PDFs, scanned invoices, and phone photos
A digital PDF normally produces the cleanest result because the characters and their page coordinates are already stored in the file. A scanned invoice depends on image quality, but a flat, high-resolution scan with strong contrast can work very well. Phone photos are convenient for receipts and field expenses, although shadows, folds, glare, perspective, and cropped edges can reduce recognition accuracy.
For better OCR invoice scanning, keep the complete page inside the frame and photograph it straight on. Use even lighting, avoid placing a receipt on a patterned surface, and make sure small totals are sharp when zoomed. Select the document language before processing. If a PDF contains a mixture of text pages and scanned pages, automatic mode can read the text layer first and apply OCR only where readable text is missing.
4. Which invoice fields can be extracted
The structured output can include invoice and due dates, invoice number, purchase order, currency, supplier, customer, shipping destination, emails, tax identifiers, payment terms, payment method, bank details, and additional labeled fields. Totals may include subtotal, tax, discount, shipping, amount paid, amount due, and the final invoice total. Full raw text is retained so information outside the standard schema is still available for review.
Line-item extraction looks for table headings such as description, item code, quantity, unit price, tax, discount, and amount. Tables vary widely, so rows can be missed when columns are not aligned, headings are unusual, or a scan is distorted. The tool warns when no table is recognized. Review quantities, decimal separators, currency, negative amounts, and tax values carefully, especially on multilingual documents or invoices using regional number formats.
5. OCR for receipts versus supplier invoices
Receipts and invoices share dates, merchants, taxes, items, and totals, but they serve different workflows. A receipt usually records a completed purchase and may have abbreviated product lines, payment-card details, tips, or a compact thermal-paper layout. An invoice requests payment and often includes supplier and customer identities, payment terms, a due date, purchase-order references, bank information, and a more detailed item table.
Use the main Invoice OCR screen when you need structured PDF or image invoice data with editable JSON and page-level source text. For a lightweight receipt-image workflow with CSV export, the related Invoice and Receipt OCR tool may be more convenient. In both cases, OCR receipt scanning should be reviewed because faded thermal paper, handwritten tips, narrow columns, and currency symbols can change the interpretation of amounts.
6. Invoice OCR in accounts payable
In an accounts-payable workflow, OCR can remove much of the first round of manual typing. A team can capture the supplier, invoice number, dates, purchase order, line items, tax, and total, then present those values to a reviewer. Structured data can support duplicate checks, purchase-order matching, approval routing, account coding, exception queues, and entry into an ERP or accounting system.
OCR AP automation still needs controls. Validate required fields, compare totals, normalize supplier identities, and flag invoices whose values do not reconcile. Separate extraction confidence from approval authority. The person or system approving payment should have access to the original document and a record of any correction. For higher-risk payments, bank-detail changes and unusual totals deserve independent verification rather than automatic acceptance from OCR output.
7. Why human review remains essential
No invoice OCR software is perfect. A clear field can be misread because of a damaged scan, decorative font, table border, stamp, handwritten note, or nearby number. The most dangerous errors are often plausible: an eight can become a six, a decimal separator can move, or a due date can be confused with an invoice date. A realistic workflow assumes that some documents will need correction.
Toolroot makes the JSON editable and includes review warnings, raw page text, and source information. Compare the invoice number, supplier, dates, currency, tax, amount due, and payment details with the source before exporting. If line items do not add up to the subtotal or the subtotal and tax do not reconcile with the total, stop the workflow and inspect the page instead of adjusting values merely to make the arithmetic fit.
8. Using invoice OCR data in Excel
The Invoice OCR screen downloads JSON rather than a native Excel workbook. JSON preserves nested information such as supplier details, tax breakdowns, page text, and line-item arrays without flattening everything into one row. You can import or transform that JSON in Excel, Power Query, a spreadsheet script, a database pipeline, or an internal application. Choose columns that match the reporting or reconciliation task instead of discarding detail too early.
For a simple invoice OCR to Excel workflow, keep one summary table for invoice-level fields and a second table for line items linked by invoice number or another stable record ID. Add source filename, review status, and import date so rows can be traced back to the document. The related receipt tool can export CSV directly, but CSV has a flatter structure and is less suitable for invoices with multiple taxes, payments, or nested parties.
9. Using the Invoice OCR API
The invoice OCR API accepts one PDF, JPG, PNG, WebP, or BMP file through a multipart POST request. Optional fields select the OCR language and force OCR for every PDF page. The JSON response contains source details, detected fields, line items, totals, page text, and warnings. Files are limited to 25 MB, and PDFs can contain up to 50 pages.
The API is different from the local browser tool. A file submitted to the API is sent to the Toolroot server for processing during that request, so review deployment, transport security, retention controls, access logs, and organizational policy before using it with production invoices. Add authentication, rate limiting, monitoring, retries, idempotency, and secure secret handling when integrating an invoice OCR API into a real accounts-payable system.
10. How to evaluate the best invoice OCR software
The best OCR for invoice processing depends on document volume, languages, layouts, latency, review requirements, security rules, and the systems that receive the data. Test software on a representative sample rather than a handful of clean examples. Include digital PDFs, scans, photos, credit notes, multi-page documents, unusual currencies, handwritten additions, dense line-item tables, and the suppliers that cause the most manual work today.
Measure field accuracy separately for invoice number, supplier, dates, purchase order, line items, tax, total, and bank details. Also measure the percentage of invoices that can pass without correction, average review time, failed-document handling, and the cost of a wrong value. Features such as confidence scores, audit trails, validation rules, custom fields, human-review queues, APIs, and native ERP connectors may matter more than a single overall OCR percentage.
11. Planning SAP and NetSuite invoice OCR workflows
Searches for OCR SAP or NetSuite invoice OCR usually describe an integration goal: extract a document, validate it, map suppliers and accounts, then create or update a payable record. Toolroot does not provide a native SAP or NetSuite connector. It produces reviewable JSON that a developer can map into an approved middleware, integration platform, or custom service after applying the destination system’s validation and authentication requirements.
Before building the connection, define required fields, vendor identifiers, tax codes, currencies, purchase-order rules, duplicate checks, attachment handling, and failure states. Do not create a payable merely because OCR returned a total. Keep the original invoice linked to the structured record, store corrections as an audit trail, and route unmatched suppliers or inconsistent totals to a reviewer. Test in a sandbox environment before sending any data to production ERP records.
12. Comparing Toolroot with Tipalti or ReadSoft OCR searches
People searching for Tipalti OCR or ReadSoft OCR are often evaluating a broader accounts-payable platform, an existing enterprise workflow, or a replacement for manual invoice capture. Toolroot is a focused extraction tool and developer API. It does not claim to reproduce vendor onboarding, approval management, payment execution, compliance, ERP administration, or the native connectors offered by full AP and document-processing products.
Use a focused tool when you need to inspect extraction behavior, process occasional documents, prototype a schema, or build a custom workflow. Evaluate an enterprise platform when you need managed approvals, large-scale operations, service commitments, implementation support, and deep integrations. Compare products using your current documents and process requirements. Brand recognition alone does not determine which system handles your layouts, languages, controls, and exception rate best.
13. AI OCR versus rule-based invoice recognition
The phrase AI OCR invoice can cover several technologies. OCR recognizes characters, layout analysis groups words and tables, rules match known labels, and machine-learning models may predict fields from visual context. Toolroot combines OCR or embedded PDF text with layout-aware parsing and multilingual label patterns. It does not ask a generative model to invent missing invoice values, and uncertain information is left for review.
Machine learning can help with diverse layouts, but every approach needs evaluation. A model may generalize well across suppliers yet make a confident mistake on a rare format. Rules can be transparent and stable but miss unfamiliar labels. Hybrid systems often use several methods plus validation and human review. Whatever technology is chosen, retain evidence for each value and monitor accuracy after suppliers change their templates.
14. Multilingual invoices and regional formats
The browser interface supports English, Spanish, French, German, Portuguese, Italian, Hindi, Arabic, Simplified Chinese, and Japanese, along with mixed modes that pair English with another language. Choose the closest mode to the document. Loading extra languages can take longer, and using an unrelated language may reduce recognition quality or turn familiar characters into incorrect symbols.
Language is only part of localization. Dates may use day-month-year or year-month-day order, decimals may use commas, and currency symbols can represent different currencies. Tax labels and invoice terminology vary by country. The parser recognizes several common patterns, but reviewers should confirm regional number formats, tax identifiers, currency, and translated field labels before the data enters financial records.
15. Privacy, security, and responsible invoice processing
In the interactive browser tool, PDF parsing, OCR, and invoice parsing run on the user’s device. OCR engine files and selected language data may download when needed, but the source invoice is not uploaded to Toolroot for that browser workflow. Clear the result and close the tab when finished, and use a trusted device when documents contain addresses, tax IDs, bank information, or other sensitive business data.
The API necessarily receives files sent to its endpoint for server-side processing, so it should be governed like any document-processing service. Organizations should assess access control, encryption, logging, data location, retention, incident response, and contractual requirements before adoption. Regardless of processing location, restrict invoice access to people and systems that need it, protect exported JSON, and verify payment-detail changes through a separate trusted channel.