This n8n workflow automates the process of capturing expense data from Telegram messages, parsing and categorizing the expenses, converting currencies when necessary, and logging the structured data into a Google Sheet. It begins with a Telegram trigger that listens for incoming messages, which could be expense notes or receipts. An AI-based agent then parses the message to extract details such as amount, description, currency, and payment method, applying category mapping rules to classify the expense accurately. If the expense involves foreign currencies like USD, SAR, or AED, it fetches real-time exchange rates to convert the amount to EGP. Additional AI models further process and refine this data, ensuring correct date formatting and structured JSON output. Finally, the parsed expense details are appended into a Google Sheet, enabling efficient expense tracking and management. This workflow is especially useful for individuals or small businesses seeking automated, real-time expense logging directly via Telegram messages.
Automated Expense Logging from Telegram Messages
Node Count | 6 – 10 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatAnthropic, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.outputParserStructured, code, googleSheets, httpRequestTool, telegramTrigger |
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