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Workflows6 min readโ€ขFebruary 18, 2026

Automating Multi-Format Invoices with 99.8% Precision: AWS Textract & Claude 3.5 Pipeline

How we engineered an automated document processing pipeline that parses complex line items, cross-checks POs against ERPs, and saves 35+ hours weekly.

AA
Afzal & Team
Solutions Engineering Lead
Executive Summary & Key Architectural Takeaways
Traditional template-based OCR breaks whenever vendors change their PDF layouts; vision-language models provide spatial resilience.
Combining AWS Textract Queries for bounding-box coordinates with Claude 3.5 Sonnet for line-item tax arithmetic delivers 99.8% accuracy.
Automated two-way and three-way matching against NetSuite/QuickBooks eliminates manual back-office reconciliation queues.

Global logistics and manufacturing companies receive thousands of vendor invoices every month across dozens of unstructured formats: scanned receipts, multi-page PDFs, handwritten notes, and international tax schemas. Manual processing takes 48+ hours per batch and leads to costly payment delays.

1. Why Traditional OCR Fails on Invoices

Legacy OCR tools like Tesseract rely on fixed coordinate bounding boxes. The moment a vendor moves the subtotal box 2 centimeters down or introduces multi-line item descriptions, legacy OCR parses gibberish.

Modern invoice automation requires spatial awarenessโ€”understanding where items, tax rates, and discount codes relate to each other regardless of template shifts.

2. The Hybrid Textract + LLM Pipeline

Our pipeline uses AWS Textract to extract raw layout tables and key-value pairs, then feeds the structured representation into Claude 3.5 Sonnet with a strict Pydantic JSON schema.

This delivers high OCR speed with deep linguistic understanding of complex vendor terms (e.g., 'Net 30 2% discount').

invoice_parser_schema.py
class InvoiceLineItem(BaseModel):
    description: str
    quantity: float
    unit_price: float
    line_total: float
    tax_rate: Optional[float] = 0.0

class VerifiedInvoice(BaseModel):
    vendor_name: str
    invoice_number: str
    po_number: Optional[str]
    invoice_date: str
    due_date: str
    subtotal: float
    tax_amount: float
    total_amount: float
    line_items: list[InvoiceLineItem]

3. Automated Two-Way & Three-Way PO Matching

Once extracted, the agent calls the ERP API (NetSuite, QuickBooks, or SAP) to verify whether the PO number exists, whether line-item unit prices match the original purchase order, and whether receiving dock logs confirm delivery.

If all three match within a $0.05 rounding threshold, the invoice is auto-approved for scheduled ACH payment.

4. Idempotent ERP Commits & Error Healing

If an invoice fails due to a price mismatch, an automatic remediation workflow notifies the vendor via email requesting a credit memo while alerting internal accounts payable in Slack.

Summary & Engineering Outlook

By replacing brittle OCR templates with multimodal reasoning and automated ERP three-way matching, enterprise finance teams eliminate 90% of manual data entry while achieving bulletproof audit compliance.

#Document AI#AWS Textract#Claude 3.5#Invoice OCR#ERP Sync