Building an AI-Powered Invoice Processor That Saves 46 Hours/Month

Every month, businesses process hundreds of invoices manually — reading PDFs, extracting data, entering it into accounting software. I built an automation that does this in seconds. The Problem A client's accounts payable team spent 200+ hours/month processing invoices: Open email attachment Read vendor name, amount, date, line items Manually enter into QuickBooks Categorize the expense File the PDF At 200 invoices/month, each taking ~15 minutes: 50 hours/month of pure data entry. The Architecture import anthropic import pdfplumber import json client = anthropic . Anthropic () def extract_invoice_data ( pdf_path : str ) -> dict : """ Extract structured data from an invoice PDF. """ with pdfplumber . open ( pdf_path ) as pdf : text = " \n " . join ( page . extract_text () for page in pdf . pages ) response = client . messages . create ( model = " claude-sonnet-4-20250514 " , max_tokens = 1024 , messages = [{ " role " : " user " , " content " : f """ Extract the following from this invoi