Finance and operations teams receive enormous volumes of documents that contain structured information locked in unstructured formats. Invoices, purchase orders, contracts, tax forms, bank statements - all contain data that needs to enter systems of record, but arrives as PDFs, scanned images, or email attachments. Intelligent Document Processing (IDP) is the set of techniques that automates that extraction.

The IDP Pipeline

A complete IDP pipeline has four stages: ingestion and classification, OCR and extraction, validation, and output.

Ingestion and classification - Documents arrive from multiple sources: email attachments, web upload, scanning stations, EDI feeds. Before extraction, documents must be classified: is this an invoice, a contract, a purchase order, a statement? Classification accuracy matters because different document types require different extraction logic. A Bedrock classification call with a sample of each document’s first page achieves 90-95% accuracy for well-defined document taxonomies. Misclassified documents route to a manual review queue.

OCR and extraction - Amazon Textract performs OCR and structural analysis. For digital PDFs (not scanned), Textract extracts text with near-perfect accuracy. For scanned documents, accuracy depends on scan quality - 300 DPI or above for production use. Textract’s table extraction preserves row/column structure, which is critical for invoice line items and financial statement data. The Queries API allows you to define specific fields you want extracted (“What is the total amount due?”, “What is the invoice date?”) and returns answers with confidence scores.

LLM-based extraction for complex documents - Contracts and freeform documents do not have predictable structure. For these, Textract provides raw text, and Bedrock (Claude) extracts structured information according to a schema you define. This is more expensive per page than pure Textract extraction but handles variability that rule-based extraction cannot.

Validation - Extracted data should be validated before it enters the system of record. Validation rules include: required fields present, numerical values within plausible ranges, date formats consistent, cross-field consistency (line item totals sum to invoice total). Validation failures route to human review with the specific failures highlighted, not to a black-box error queue.

Invoice Processing in Detail

Invoice extraction is the highest-volume IDP use case. A typical enterprise processes thousands to hundreds of thousands of invoices per year. The key fields to extract:

  • Vendor identification (name, VAT number, bank details)
  • Invoice metadata (number, date, due date, currency)
  • Line items (description, quantity, unit price, VAT rate, line total)
  • Totals (subtotal, VAT amount, total due)

For invoices from known vendors, template matching improves accuracy and reduces cost: store field locations for frequently-processed vendor formats and apply them directly rather than running full AI extraction every time.

Contract Analysis

Contract analysis has different requirements than invoice processing. Rather than field extraction, the goal is typically clause identification and risk flagging: does this contract contain a non-standard limitation of liability clause? What are the payment terms? Does it include auto-renewal language?

A Bedrock-based contract analysis workflow processes the full contract text and returns a structured summary with flagged clauses and their locations in the document. For legal review workflows, this reduces the time to first-pass review significantly - a lawyer reviewing a 40-page contract with a pre-generated summary can focus on flagged items rather than reading linearly.

Cost Optimization

IDP costs are primarily driven by page volume. Textract pricing is per page; Bedrock costs are per token. For high-volume pipelines, optimization strategies include: caching extraction results for re-processed documents, using lower-cost models for classification and validation, reserving higher-cost models for complex freeform extraction. A well-optimized pipeline for standard invoice processing typically costs less than 0.05 EUR per document at scale.