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8d • General Discussion
Invoice extraction with variable formats - Every builder's nightmare 🔥
THE PROBLEM
Pre-trained models break on new formats
Template approaches need constant updates
Hardcoded extraction fails on layout changes
Custom ML requires training data and time
THE BETTER APPROACH
Stop trying to match templates.
Define what fields you need.
Let AI figure out the layout.
Use extraction with JSON Schema:
You define structure once (invoice number, date, items, totals)
API extracts those fields regardless of layout
Returns consistent JSON every time
REAL EXAMPLE
Client with 12 vendor invoice formats:
Single column layouts
Two column layouts
Tables with merged cells
Handwritten notes mixed in
Multi-page with scattered totals
Different languages
Old approach: Build template for each format (12 templates to maintain)
New approach: One schema, works on all formats
THE SCHEMA
```json
{
"invoice_number": "string",
"date": "string",
"vendor": "string",
"line_items": [
{
"description": "string",
"quantity": "number",
"price": "number"
}
],
"subtotal": "number",
"tax": "number",
"total": "number"
}
```
Send any invoice + this schema.
Get back consistent JSON.
RESULTS
Handles any invoice format: Yes
Accuracy: 96.8%
Maintenance: Zero (no templates to update)
Setup time: Define schema once (10 minutes)
WORKS WITH n8n, Make, Zapier
HTTP Request node or community node
Send PDF + schema
Get structured JSON back
Route to your system
Current clients:
8 using this for invoices
4 for contracts
3 for medical forms
2 for receipts
Average accuracy: 96.2%
Template maintenance: $0
The key: Don't train on layouts.
Define what fields you need.
What variable format extraction are you fighting with templates?
4
1 comment
Invoice extraction with variable formats - Every builder's nightmare 🔥
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