This workflow automates the process of capturing, parsing, and summarizing receipts received through Telegram. It enables users to send images or text descriptions of expenses, which are then extracted using OCR and AI models. The receipt data is structured to include store details, transaction date and time, individual items, total amount, and expense category. The workflow intelligently routes inputs based on whether they are images or text, and uses AI classification to categorize expenses or incomes. It also detects invalid inputs, providing error messages to the user. The final output is a clear, formatted expense summary sent back to the user via Telegram, making expense management more efficient and accessible.
Automated Receipt Processing and Expense Reporting via Telegram
Node Count | >20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatOpenRouter, @n8n/n8n-nodes-langchain.outputParserStructured, code, httpRequest, if, n8n-nodes-tesseractjs.tesseractNode, set, stickyNote, telegram, telegramTrigger |
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