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AI Resume Parsing and Client Usage Billing Tracking

This workflow provides AI-driven resume parsing services, capable of automatically converting uploaded PDF resumes into structured JSON format, thereby enhancing data processing efficiency. At the same time, the system accurately tracks each client's token usage and associated costs in the AI service, recording this information in Google Sheets for transparent billing. It automatically summarizes client data each month and generates electronic invoices, greatly simplifying the financial management process, making it suitable for various scenarios such as human resources, recruitment, and finance teams.

Workflow Diagram
AI Resume Parsing and Client Usage Billing Tracking Workflow diagram

Workflow Name

AI Resume Parsing and Client Usage Billing Tracking

Key Features and Highlights

This workflow offers a comprehensive AI-driven service for uploading and parsing resume (CV) PDF files. It automatically extracts the content from uploaded resumes and structures it into JSON format for easy downstream processing. Additionally, it leverages a custom Langchain Code node to capture token usage and cost metadata for each AI call, automatically logging this data into Google Sheets. This enables precise client usage billing and cost tracking. At the end of each month, the workflow aggregates client usage data and generates electronic invoices, facilitating financial automation.

Core Problems Addressed

  • Automates conversion of resume PDFs into structured data, significantly improving manual processing efficiency.
  • Accurately tracks token consumption and corresponding costs per client, ensuring transparent multi-client billing.
  • Eliminates complex dependencies by integrating custom subnodes with Google Sheets, enabling low-barrier usage and cost monitoring.
  • Automatically summarizes and sends monthly invoices, reducing manual accounting and invoicing workload.

Use Cases

  • Automated resume data processing for HR and recruitment platforms.
  • SaaS providers offering AI data extraction APIs, implementing client usage-based billing.
  • Enterprises or teams requiring client billing based on AI call costs.
  • Multi-client systems aiming for transparent management of AI service calls and associated expenses.

Main Workflow Steps

  1. Form Submission Trigger: Clients upload resume PDFs via an n8n form and acknowledge the billing terms.
  2. PDF Parsing: Extract text content from the uploaded PDF files.
  3. Variable Assignment: Set workflow ID, execution ID, client ID, and other logging attributes.
  4. Custom LLM Subnode Invocation: Use the OpenAI GPT-4o-mini model to parse text into structured JSON while capturing token usage metadata.
  5. Resume Data Extraction: Extract detailed resume information based on a predefined JSON schema.
  6. Result Display: Return the parsed JSON data to the uploading user.
  7. Usage Data Logging: Append token usage and cost data to Google Sheets.
  8. Monthly Scheduled Trigger: At month-end, filter client usage records from Google Sheets.
  9. Data Aggregation: Summarize total tokens used and costs for the month.
  10. Automated Invoice Sending: Email detailed monthly invoices to clients via Gmail.

Systems and Services Involved

  • n8n Form Trigger: Provides file upload and user interaction interface.
  • OpenAI GPT-4o-mini Model: Language model for extracting resume information.
  • Langchain Code Node: Custom code node for tracking token usage and calculating costs.
  • Google Sheets: Storage for client usage logs and billing data.
  • Gmail: Automated dispatch of monthly client invoices.

Target Users and Value Proposition

  • AI Service Providers: Precisely track client token usage and costs to support flexible billing and cost control.
  • Recruitment Firms and HR Teams: Rapidly convert large volumes of resumes into structured data for easier screening and management.
  • Finance and Operations Teams: Automate client usage aggregation and invoice generation, reducing manual effort.
  • Technical Teams and Developers: Demonstrate how to combine n8n with Langchain code nodes for advanced AI call monitoring and billing management.

This workflow is exclusively compatible with the self-hosted version of n8n, as the Langchain Code node is a self-hosted feature. By integrating AI parsing with cloud spreadsheet storage, it achieves seamless automation of resume parsing and cost tracking, greatly enhancing operational efficiency and transparency. You are welcome to explore the example Google Sheets log here: Client Usage Log for detailed data insights.

AI Resume Parsing and Client Usage Billing Tracking