CASE STUDY 09

High-Volume Invoice and Email Processing Pipeline

Pipeline that processes multi-hundred-page invoices with 500-800 line items each, extracting structured data into a database with validation.

Industry: Operations / Finance ops Timeline: 6 weeks Document ProcessingWorkflowsEmail Automation
High-Volume Invoice and Email Processing Pipeline — architecture diagram
SYSTEM ARCHITECTURE

The pain

The team was receiving massive invoices from suppliers. Sometimes 400+ pages with line items spread across hundreds of pages. A bookkeeper was manually transcribing them into the accounting system. One invoice took 6-8 hours.

Errors were frequent. The backlog was growing faster than they could process.

They needed a system that could parse the invoices, extract structured line items, validate them, and surface only the exceptions for human review.

What I built

n8n email parser

Classifies incoming emails by sender, attachment type, subject.

OCR layer

Hybrid Tesseract + Claude vision for difficult layouts.

Claude extractor

Reads multi-page PDFs and returns structured line items with confidence scores.

Validation engine

Cross-checks line items against catalog data, flags anomalies, routes for review.

Database writer

Persists validated rows into Airtable + Supabase with full audit trail.

Asana queue

Exception tasks for the bookkeeper to review daily.

Daily error report

Summarizing extraction issues, sent to the operations lead.

Outcome

12min
Per invoice, down from 6-8 hours
30hrs/wk
Bookkeeper time reclaimed
98.7%
Line-item extraction accuracy
3wks
To clear the entire backlog

Stack

n8nAirtableSupabaseAsanaJavaScriptPythonTesseractClaude visionClaudeEmail parsing
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