This workflow automatically extracts invoice data from PDF attachments received via Gmail. It uses AI to parse structured fields like PO numbers, line items, and totals, then stores this information neatly into a Google Sheet and labels the processed email.
This workflow monitors your Gmail for new emails containing PDF invoice attachments. It uses AI to extract key financial data such as company information, invoice numbers, line items, and taxes from the PDF. Finally, it creates a new Google Sheet, populates it with the extracted data, and organizes the file in Google Drive for accounting purposes.
This workflow automatically triggers when a new PDF invoice is uploaded to a specified Google Drive folder. It extracts key invoice details using AI, logs this data into a Google Sheet, and then generates and sends an email alert to the billing team via Gmail with a summary of the processed invoice.
This workflow automatically processes new PDF invoice uploads to a Google Drive folder. It extracts key details like vendor, amount, and dates using AI after performing OCR on the PDF, then logs this structured data into an Airtable database or Google Sheet. Finally, it moves the processed PDF to a 'Done' folder, streamlining invoice management.
This workflow automates invoice processing by monitoring a Google Drive folder for new PDF invoices. Upon detection of a new PDF, it extracts text content using OCR, then uses AI to parse and extract key invoice details like invoice number, date, and total amount. Finally, it stores the extracted, structured data into a Google Sheet for easy access and reporting.
This workflow monitors for new customer support emails in Gmail. It uses a primary AI model (Gemini) to generate replies. If the primary AI fails or for complex queries, it intelligently falls back to a secondary AI model (GPT). Finally, it sends the AI-generated reply and logs all interaction details into a Google Sheet for tracking.
This workflow triggers when a new email containing an inbound order is received in Gmail. It then uses an AI model to extract key order details such as PO number, delivery date, SKU ID, and quantity from the email body. Finally, the extracted information is automatically added as a new row to a specified Google Sheet for logistics tracking.