Extract Spend Details (Template)
This workflow automatically retrieves attachments from tagged emails in Gmail, parses PDF invoices and payment documents, and uses an AI language model to intelligently analyze the email content to extract transaction details. Ultimately, it automatically writes structured transaction information such as date, merchant, and amount into Google Sheets, significantly enhancing the efficiency and accuracy of financial data organization, making it suitable for the financial management needs of businesses, individuals, and accountants.
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Workflow Name
Extract Spend Details (Template)
Key Features and Highlights
This workflow automatically extracts attachments from labeled emails in Gmail (invoices and payment-related emails), parses PDF-format invoices and payment documents, and combines data from the email’s HTML content to extract detailed spend information. Leveraging AI language models from Google Gemini and Groq, it intelligently analyzes email content to structurally extract transaction date, merchant name, amount, category, currency, and credit card information. The structured data is then automatically appended to Google Sheets, creating an electronic record that facilitates financial analysis and accounting management.
Core Problems Addressed
Traditional financial data entry is cumbersome, with diverse formats in email attachments and content, making manual organization time-consuming and error-prone. This workflow automates the extraction and intelligent parsing of multi-source invoices and payment emails, standardizing the output and significantly improving the efficiency and accuracy of financial data organization.
Application Scenarios
- Automation of corporate or personal financial management
- Parsing credit card transaction emails and statements
- Automatic archiving and analysis of electronic invoices and payment notifications
- Support tool for finance departments or accounting personnel
Main Process Steps
- Monitor emails with specified labels in Gmail and automatically download invoice and payment email attachments.
- Extract text content from PDF attachments.
- Categorize emails by source (multiple payment info emails, single payment info emails, invoice emails) for differentiated processing.
- Extract marked spend detail data from the email’s HTML content.
- Use AI language models (Google Gemini Chat Model and Groq Chat Model) to parse email content and convert it into structured accounting data.
- Validate and format AI output through a structured output parser.
- Append the finalized transaction records to a Google Sheets spreadsheet for easy subsequent management and analysis.
Involved Systems and Services
- Gmail (email trigger and attachment download)
- PDF parsing node (Extract from File)
- HTML content extraction (CSS selector extraction)
- Google Gemini Chat Model and Groq Chat Model (AI language model parsing)
- Google Sheets (data storage)
- Built-in n8n nodes (Switch branching, Set data, Merge, etc.)
Target Users and Value
- Finance staff and accounting assistants: automate processing of large volumes of electronic bills and payment notifications to improve work efficiency.
- Business managers: obtain real-time structured financial data to support budgeting and reimbursement decisions.
- Freelancers and small business owners: simplify accounting workflows and reduce manual costs.
- Developers and automation enthusiasts: customize parsing rules and output formats as needed for flexible expansion.
By integrating automated email extraction, AI-powered intelligent parsing, and cloud-based spreadsheet writing, this workflow provides an efficient and accurate automated solution for financial spend detail processing. It greatly simplifies the traditionally tedious steps of financial data organization and is suitable for a wide range of financial management scenarios.
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Extract Spend Details (Template)
This workflow is designed to automate the processing of financial emails. It can extract emails marked as "Invoice" and "Payment" from Gmail, download attachments, and parse PDF content. Using advanced AI language models, it extracts transaction information and organizes it in a structured manner. Finally, the cleaned data is automatically written into Google Sheets. This process significantly reduces the workload of manual searching and data entry, improves data accuracy and management efficiency, and is suitable for the financial departments of enterprises, as well as for individuals and small businesses in financial management.
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