Stop Manually Entering Data from PDFs and Documents
DigiParser automatically extracts structured data from invoices, bank statements, purchase orders, and any document — then sends it to your ERP, spreadsheet, or database. 99.7% accuracy. No templates required.
No credit card required · 20 free documents included
The Manual Data Entry Problem
- Hours spent copying data from PDFs into spreadsheets
- Human error rate of ~1% means constant corrections
- Team bottleneck during invoice-heavy periods
- No way to scale without hiring more people
- Staff doing repetitive work instead of analysis
With DigiParser
- Documents processed in under 10 seconds each
- 99.7% accuracy — no correction queue
- Handles thousands of documents simultaneously
- Volume scales without adding headcount
- Team focuses on exceptions and analysis
Extract Data from Any Document Type
DigiParser recognizes hundreds of document formats automatically — no template setup required for common types.
Invoices & AP Documents
- Vendor name & address
- Invoice number & date
- Line items, quantities, prices
- Tax, discount, total amount
Bank Statements
- All transactions
- Dates & descriptions
- Debit & credit amounts
- Opening & closing balance
Purchase Orders
- PO number & date
- Supplier details
- Line items & SKUs
- Delivery terms
Shipping & Logistics
- Shipper & consignee
- Container & cargo details
- Tracking numbers
- Delivery addresses
Receipts & Expenses
- Merchant & date
- Items purchased
- Tax & totals
- Payment method
Resumes & HR Documents
- Candidate name & contact
- Work experience
- Skills & education
- Certifications
Contracts & Legal
- Parties & signatures
- Key dates & terms
- Obligations & clauses
- Payment terms
Custom Document Types
- Any structured form
- Multi-page reports
- Industry-specific templates
- Define your own schema
Manual Data Entry vs. Automated Extraction
The numbers make the case clearly.
| Manual Entry | DigiParser (Automated) | |
|---|---|---|
| Speed | 20–40 minutes per document | Under 10 seconds |
| Accuracy | ~92% (human error rate ~1 in 12) | 99.7% consistent |
| Scale | 1 person = ~50 docs/day | Thousands per hour |
| Cost | $15–40/hour labor cost | Fraction of labor cost |
| Availability | Business hours only | 24/7, weekends included |
| Auditability | Hard to trace errors | Full extraction log |
How Automated Data Extraction Works
Document In
PDF, image, or email arrives via upload, email forward, API, or Zapier trigger.
AI Reads & Extracts
OCR + layout analysis + named-entity extraction identify every field in your schema.
Validation
Extracted data is cross-checked for format validity and confidence scoring.
Data Out
Structured JSON, CSV, or Excel exported — or pushed directly to your ERP, spreadsheet, or CRM.
Automated Data Extraction — FAQ
What is automated data extraction?
Automated data extraction is the use of software — typically AI or OCR — to read documents (PDFs, images, emails) and pull out specific pieces of information without human involvement. Instead of someone manually reading an invoice and typing the vendor name, amount, and line items into a spreadsheet, automated extraction does this in seconds with high accuracy.
What types of documents can DigiParser extract data from?
DigiParser extracts data from invoices, bank statements, purchase orders, receipts, contracts, resumes, bills of lading, tax forms, identity documents, insurance forms, utility bills, and any custom document type you define. Both digital PDFs and scanned/photographed documents are supported.
How accurate is automated data extraction?
DigiParser achieves 99.7% extraction accuracy on standard business document formats. Manual data entry typically has an error rate of around 1% (1 in 100 fields wrong) due to human fatigue and misreading. Automated extraction eliminates this error class entirely for structured documents.
How does automated data extraction work technically?
DigiParser uses a multi-layer AI pipeline: first, OCR converts the document into machine-readable text; then, a layout analysis model identifies the structure (tables, fields, headers); finally, a named-entity extraction model maps content to your defined schema. The result is structured JSON matching your data model.
Can data extraction work on scanned or handwritten documents?
Yes. DigiParser's OCR layer reads scanned PDFs, photographs, and even handwritten forms (Intelligent Character Recognition). Accuracy is highest on clean scans but the system handles moderate-quality documents well.
Where does the extracted data go?
Extracted data can be exported to Excel, CSV, JSON, or pushed directly to Google Sheets, QuickBooks, Xero, Salesforce, HubSpot, Airtable, or any app via the REST API or Zapier. Data can also be sent via webhook to your own backend in real time.
How long does it take to set up automated data extraction?
For standard document types (invoices, bank statements, resumes), DigiParser requires zero setup — the AI recognizes these formats automatically. For custom document types, you define your extraction schema in minutes using the visual schema builder, then test on a sample document.
What is the ROI of automated data extraction?
A typical finance team processing 500 invoices per month at 20 minutes each = 167 hours of manual entry per month. At $25/hour that's $4,175/month in labor. DigiParser processes the same 500 invoices in under an hour, at a fraction of that cost — with higher accuracy.
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Get Started with DigiParser
Ready to automate your document processing? Start your free trial today and discover how DigiParser can transform your workflow.