Pull tables, fields, and line items out of any PDF, native or scanned, without templates or manual setup. Built on Lido’s AI extraction engine.
Upload any document — PDF, scan, or photo — and get structured data back immediately. No setup, no templates, no waiting.
Upload PDF files directly, or connect cloud drives, email inboxes, and your own application via the REST API—new PDFs flow in automatically.
The PDF data extractor reads each file contextually, pulling structured fields from invoices, statements, contracts, and forms in any layout without templates.
Route structured output to Excel, Google Sheets, databases, or downstream systems via API. Set up once and every new document is processed automatically.
“We process invoices from over 200 vendors with completely different layouts. This PDF data extractor handled them all on the first upload without any configuration.”
“Manual data entry was eating 15 hours a week. We cut that to under an hour by letting the AI extract everything into a spreadsheet automatically.”
“The confidence scoring is what sold us. We set a 95% threshold and only review flagged fields instead of spot-checking everything.”
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.
Last updated: August 2026
A PDF data extractor is software that reads PDF files and pulls specific fields—totals, dates, parties, line items, entire tables—into structured formats such as spreadsheet rows, CSV, or JSON. The PDF is the default container for business paperwork: invoices, bank statements, purchase orders, contracts, and reports almost always arrive as PDFs, which makes the format the natural starting point for any data entry automation effort.
The difficulty is that PDF was designed for faithful display, not data exchange. A PDF stores characters and their positions on a page; it has no concept of a field called “invoice total” or a table with rows and columns. Extracting data therefore means reconstructing meaning from layout—and doing it across files that look completely different from one sender to the next.
Basic converters and copy-paste workflows treat every page the same way, which is why exported tables collapse into misaligned columns and headers merge with data rows. Template-based PDF extractors improved on this by letting administrators draw zones on a sample file—the total lives here, the date there—but every new vendor layout meant another template to build and maintain, and the library grew without end.
Scanned PDFs add a second layer of difficulty. When the page is an image rather than digital text, there is nothing to copy at all, and OCR quality determines everything downstream. Systems that bolt OCR onto a rigid template pipeline inherit the weaknesses of both: recognition errors compound with layout drift, and accuracy degrades exactly when volume makes manual review impractical.
Layout-agnostic AI extraction addresses the problem at its root. Rather than depending on coordinates or training samples, the AI reads each page contextually—understanding that a value labeled “Total” is a total regardless of where it appears. Lido applies this approach to PDFs directly: it detects whether a file is native or scanned, reads it contextually, and returns structured data with field-level confidence scores on the first upload—no templates or training data. For a detailed look at why template-based approaches break down at scale, see The Problem with Template-Based Document Extraction on the Lido blog.
Explore how the PDF data extractor handles your specific needs: review the full feature set for extraction capabilities, see available integrations with downstream systems, and browse use cases across industries and document types.
A PDF data extractor is software that reads PDF files, both digitally generated and scanned, and pulls specific fields, tables, and line items into structured data like spreadsheet rows, CSV, or JSON. Modern PDF data extractors use AI vision models that understand page layout and context, so they do not require templates or manual zone configuration. Lido reads any PDF layout on the first upload, whether the file is a native digital PDF or a scanned image saved as a PDF.
Both. Native digital PDFs contain a text layer that can be read directly, while scanned PDFs are page images that require OCR before any data can be extracted. A modern PDF data extractor detects which kind of file it has received and applies AI-powered OCR automatically when the page is an image. Lido processes native PDFs, scanned PDFs, and photographed documents saved as PDFs with the same layout-agnostic engine.
AI-based PDF data extraction typically achieves 95 to 99 percent accuracy on well-structured documents, which matches or exceeds manual data entry accuracy. The advantage is consistency: AI does not experience fatigue or make transcription errors that increase with volume. For edge cases like handwritten text or damaged scans, confidence scoring flags uncertain fields for human review rather than guessing silently. Lido provides confidence scores on every extracted field so teams can set review thresholds appropriate for their accuracy requirements.
Table extraction fails in generic converters because a PDF stores visual character positions, not table semantics. An AI PDF data extractor reconstructs each table by recognizing rows, columns, headers, and merged cells contextually, then outputs clean spreadsheet rows. Lido preserves line-item structure across multi-page tables, exports to Excel, Google Sheets, CSV, or JSON, and flags low-confidence cells for review instead of silently guessing.
Template-based tools require a separate configuration for every layout, which becomes unmanageable when PDFs arrive from many different vendors, banks, or customers. Layout-agnostic extractors use AI models that identify fields by their semantic meaning rather than fixed coordinates, so a new invoice format or an unfamiliar statement works on the first file without any setup. Lido uses this approach and adds AI columns that let users define custom extraction rules in plain English.
Start free with 50 pages. Upgrade when you’re ready.
Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine
50 free pages. No credit card required.