I Extended The Gmail Agent Template To Actually Read Invoices (Not Just Forward Them) 🔥
Grabbed the community's 'Gmail AI Agent' template. It categorized emails perfectly. But client asked: 'Can it extract invoice data too?' Added 3 nodes. Now it does. THE BASE TEMPLATE: Using the popular 'Gmail AI Agent' (2,000+ downloads from community). Categorizes emails, drafts responses. Works perfectly for text. But ignores PDF attachments completely. CLIENT'S REQUEST: 'When invoice email arrives, can the agent extract vendor name, amount, due date? Right now it just forwards the email.' THE EXTENSION (3 NEW NODES): NODE 1 - IF NODE: Check for PDF attachment Triggers when email has .pdf file attached. Routes to document processing branch. NODE 2 - DOCUMENT PROCESSING NODE: Parse Invoice Configuration: Extract Structured Document mode. JSON Schema for invoice data (vendor, amount, date, invoice_number). Returns structured data. NODE 3 - SET NODE: Format for Agent Takes extracted invoice data, formats as clear text summary for agent to use. NODE 4 - ADDITIONAL TOOL: Give agent new capability Tool name: 'Extract Invoice Data' Tool description: 'Extracts vendor, amount, date, and invoice number from PDF invoices' Tool input: Email with PDF attachment Tool output: Structured invoice data THE RESULT: Agent now responds: 'I found an invoice from Vendor X for $1,245.50, due March 15. I've added it to your tracking sheet in row 47.' Before extension: Agent could only read email text, forwarded invoices manually. After extension: Agent extracts data, logs automatically, provides summary. IMPLEMENTATION TIME: 25 minutes to extend the base template. No need to rebuild agent from scratch. THE NUMBERS: - Processes 80+ invoice emails monthly - Saves 12 minutes per invoice (no manual entry) - Client processes $120K invoices monthly through agent - Zero manual data entry needed CONFIGURATION DETAILS: Document processing node settings: Use 'Extract Structured Document' operation. Define JSON Schema with required fields. Set confidence threshold at 0.85. Route low-confidence extractions to review queue.