This n8n workflow streamlines the process of receiving, parsing, and managing receipts via Telegram. It starts by listening for user messages through a Telegram trigger, then determines if the message contains an image or text input. If it’s an image, OCR (Optical Character Recognition) is used to extract text from the receipt. Alternatively, text input is processed directly. The extracted data is then sent to an AI agent for structured parsing and validation. The workflow generates summary messages, notifies users with errors or acknowledgments, and saves receipts to Google Drive. Additionally, expense details are logged into Google Sheets for record-keeping. This automation is valuable for expense tracking, simplifying receipt uploads, and integrating AI-powered data extraction into personal or business workflows.
Automated Receipt Processing and Expense Reporting
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.lmChatMistralCloud, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.lmChatOpenRouter, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.outputParserAutofixing, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.toolThink, code, dateTimeTool, executeWorkflow, executeWorkflowTrigger, googleDrive, googleSheets, httpRequest, if, merge, n8n-nodes-tesseractjs.tesseractNode, set, stickyNote, telegram, telegramTrigger |
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