Extract Spend Details (Template)

Workflow Name

Extract Spend Details (Template)

Key Features and Highlights

This workflow automatically captures emails labeled as “Invoice” and “Payment” from Gmail, downloads attachments, and extracts invoice and payment information from PDFs. It leverages advanced AI language models (Google Gemini and Groq Chat) for content parsing, structurally extracting transaction date, service name, transaction details, amount, category, currency, and credit card information. The cleaned and organized data is then automatically written into Google Sheets, facilitating financial management and subsequent analysis. It supports multiple email formats and recognition of multiple payment entries, with customizable parsing rules and output formats.

Core Problems Addressed

• Automates the processing of complex financial emails, reducing manual searching and data entry of invoices and payment information
• Resolves challenges in extracting transaction data from various email formats, improving data accuracy and completeness
• Enables automatic association and archiving of invoice and payment data, enhancing financial data management efficiency
• Utilizes AI-powered intelligent parsing to structure complex text, facilitating subsequent financial analysis and report generation

Application Scenarios

• Corporate finance departments needing to automatically organize customer or supplier invoice and payment emails
• Individuals or small businesses managing credit card statements and expense records automatically
• Financial outsourcing service providers processing bulk client invoice and payment emails
• Any scenario requiring automatic import of financial information from emails into spreadsheets for unified management

Main Process Steps

1. Email Retrieval: Use Gmail triggers to monitor emails with specified labels for invoices and payments, automatically downloading attachments
2. Attachment Parsing: Extract content from PDF attachments and decrypt if password-protected
3. Email Content Classification: Use Switch nodes to determine email source and content type, differentiating multiple payments, single payments, and invoice emails
4. Data Extraction: Apply custom CSS selectors to extract expense details from HTML, combined with AI language models for structured parsing of email text
5. Data Organization: Standardize data fields (date, amount, category, etc.) based on email type and parsing results
6. Data Merging: Consolidate parsing results from different sources and formats
7. Data Writing: Append structured financial data into Google Sheets, supporting financial reporting and further processing

Involved Systems or Services

• Gmail: Email triggers to fetch emails and attachments with specified labels
• PDF Parser: Extract invoice and payment information from attachments
• AI Language Models: Google Gemini Chat, Groq Chat for natural language understanding and structured output
• Google Sheets: Storage and display of financial data
• n8n Nodes: Switch, Set, Merge, Split Out, and other workflow control and data processing nodes

Target Users and Value

• Finance personnel and accountants, reducing manual entry and improving efficiency and accuracy
• Business managers, gaining real-time visibility into financial expenditure details to support decision-making
• Automation enthusiasts and IT professionals, enabling rapid setup of automated email financial data processing systems
• Small and medium-sized business owners, achieving low-cost, efficient financial data automation and saving labor costs

This workflow provides an end-to-end solution for financial automation by integrating automated email capture, AI-powered intelligent parsing, and cloud data storage, significantly enhancing the intelligence and convenience of financial data processing.