AI Agent: Expense Tracker in Google Sheets and n8n Chat
This workflow allows users to interact with a chatbot, enabling them to input expense information in natural language. The system automatically parses this information and converts it into structured data, which is saved in real-time to Google Sheets. It utilizes large language models to extract the amount, description, and date of expenses, significantly enhancing the efficiency and accuracy of expense recording. The workflow supports multi-turn conversations and memory functions, helping users manage personal or team expenses conveniently and quickly, making it particularly suitable for users who need to record expenses rapidly.
Workflow Name
AI Agent: Expense Tracker in Google Sheets and n8n Chat
Key Features and Highlights
This workflow enables automatic parsing of user-entered expense information in natural language through interaction with a chatbot, converting it into structured data that is saved in real-time to Google Sheets. Leveraging large language models (LLMs), it automatically extracts expense amounts, descriptions, and dates, significantly enhancing the convenience and accuracy of expense tracking. It supports multi-turn conversations with memory capabilities to ensure coherent chat context.
Core Problems Addressed
Traditional expense recording often relies on manual input, which is time-consuming, labor-intensive, and prone to errors. This workflow eliminates the hassle of manual entry by utilizing natural language understanding and automated processes, helping users quickly and accurately manage personal or team expense data.
Application Scenarios
- Daily expense recording and management for individuals or small teams
- Sales and finance personnel requiring rapid expense entry
- Expense reimbursement data collection in remote work environments
- Automated office scenarios integrating chat tools for expense tracking
Main Workflow Steps
- The user sends a message containing expense information via the chat interface (e.g., “car wash; 59.3 usd; 25 jan 2024”).
- The “Chat Message Received” node is triggered, invoking the AI Agent node to process the input.
- The OpenAI Chat model parses the user text and calls a sub-workflow to convert the text into JSON-formatted expense data (including amount, description, and date).
- The structured data is passed to the Google Sheets node and automatically appended as a new row.
- The system returns a confirmation message informing the user that the expense has been successfully saved and displays the saved result.
Involved Systems and Services
- Google Sheets (for data storage and management)
- OpenAI (GPT models for natural language parsing and understanding)
- n8n workflow platform (for automated process orchestration)
- Language model agent (AI Agent) and memory management (Window Buffer Memory) nodes, enabling intelligent dialogue and context retention
Target Users and Value Proposition
Ideal for individuals, freelancers, and small teams who want to easily record and manage expenses via a chat interface. Without requiring complex spreadsheet operations, anyone can log expenses through simple natural language input, improving work efficiency, reducing errors, and facilitating financial statistics and report generation. This workflow is especially suitable for users accustomed to working with chat tools who seek automated and intelligent financial management.