Classify incoming documents as invoices, extract key fields—vendor, number, date, amount, line items—and route them for processing, all without manual sorting.
Upload any document — PDF, scan, or photo — and get structured data back immediately. No setup, no templates, no waiting.
Drag and drop files, connect a cloud drive, or set up email auto-forwarding. Any file format works—PDF, JPEG, PNG, TIFF, or digital documents.
The AI identifies fields by context and meaning, not fixed coordinates. Names, dates, amounts, and custom fields are extracted automatically.
Get structured output in Excel, Google Sheets, CSV, or JSON. Use the REST API for direct integration into your systems.
“Our AP inbox receives 200 documents per day and only half are actual invoices. Automated recognition separates invoices from everything else, saving our team 2 hours of daily sorting work.”
“The credit note detection is valuable. Misclassifying a credit note as a standard invoice used to create payment errors. Now the system identifies the document type correctly before extraction begins.”
“We receive invoices in five languages from vendors across Europe. The recognition handles all of them without language-specific configuration, which simplified our AP workflow significantly.”
Invoice recognition is the first step in any automated accounts payable workflow. Before data can be extracted from an invoice, the system must first recognize that a document is an invoice, distinguish it from purchase orders, delivery notes, statements, and other business documents, and identify the invoice type—standard invoice, credit note, debit note, or proforma. This classification step is often overlooked, but it determines the accuracy and efficiency of everything that follows in the AP pipeline.
In practice, AP departments receive a mixed stream of documents. A shared AP email inbox might contain vendor invoices, account statements, payment remittances, shipping notifications, and marketing materials. Manual sorting of this document stream wastes time and creates misrouting errors. AI-powered invoice recognition classifies each incoming document automatically, identifying invoices with high confidence and routing non-invoice documents to the appropriate queue. This eliminates the manual triage step that is the first bottleneck in most AP workflows.
Invoice recognition also encompasses the intelligence needed to extract data from recognized invoices. Once a document is confirmed as an invoice, the system identifies and extracts vendor name, invoice number, date, line items, tax amounts, total, payment terms, and bank details. Lido combines document classification and field extraction in a single pass, meaning an invoice is recognized, classified, and fully extracted within seconds of arriving in the system.
Organizations evaluating invoice recognition solutions should consider classification accuracy across document types, extraction accuracy on invoice fields, support for international invoice formats, and integration with AP workflow platforms. Lido provides confidence scores on both the classification and extraction, enabling rules-based routing where high-confidence invoices are processed automatically and uncertain documents are queued for human review.
Audited controls over a sustained period, not a point-in-time check.
Bank-grade encryption at rest and TLS 1.2+ in transit.
Documents deleted within 24 hours. No copies retained.
Invoice recognition is the automated process of identifying documents as invoices, classifying them by type (standard invoice, credit note, debit note, proforma), and extracting key fields. It combines document classification with data extraction to enable end-to-end AP automation.
AI-powered recognition classifies each document in a mixed stream—identifying invoices, separating them from purchase orders, statements, and other documents, and routing each to the appropriate processing queue. This eliminates manual document sorting.
The system extracts vendor name, invoice number, date, line items with descriptions and amounts, tax details, total amount, payment terms, and bank or payment details. All fields include confidence scores for quality assurance.
Invoice classification typically achieves over 98 percent accuracy, and field extraction achieves 95 to 99 percent accuracy on standard invoice formats. Confidence scoring enables rules-based routing where uncertain documents receive human review.
Yes. The AI recognizes and extracts data from invoices in multiple languages, including invoices with mixed-language content. This is particularly valuable for organizations with international vendor bases.
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Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine
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