This workflow automates the extraction, analysis, and recording of financial transaction data from receipt images sent via Telegram. It begins when a user uploads a receipt image to a Telegram bot, which then retrieves the image file from Telegram’s servers. The image is processed using Google’s Vision OCR API to extract text, which is then fed into a Large Language Model (LLM) for structured data parsing, including details like date, store information, invoice number, and individual items. The parsed data is cleaned and stored in a Google Sheets document, creating a detailed financial record. Additionally, the workflow offers interactive features: it can respond to user queries about the stored data by engaging in conversation using AI chat models, providing summaries or specific details in easy-to-understand formats. This setup is ideal for automating expense tracking, financial auditing, or creating a hands-free digital receipt management system for small businesses or accounting teams.
Automated Financial Receipt Processing with OCR and AI
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatOpenRouter, @n8n/n8n-nodes-langchain.memoryBufferWindow, @n8n/n8n-nodes-langchain.outputParserStructured, code, googleSheets, googleSheetsTool, httpRequest, if, set, splitOut, stickyNote, telegram, telegramTrigger |
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