Use this powerful n8n workflow to instantly analyze uploaded PDF invoices via Telegram using OpenAI's capabilities. Automate data extraction and receive structured results.
Download this n8n workflow template and start using it instantly.
Finance Departments: Those needing rapid, automated extraction of invoice details without manual input.
Small Businesses & Accountants: Users who manage a high volume of vendor invoices and rely on Telegram for communication.
n8n Automation Specialists: Users looking for advanced n8n templates integrating Telegram, file operations, and OpenAI for complex document processing.
Developers & Integrators: Teams building intelligent document processing systems using the n8n platform.
Handling invoices often involves tedious manual data entry, which is prone to errors. This specific n8n workflow template solves this challenge by transforming your Telegram chat into an intelligent document processor. When an invoice (e.g., PDF) is dropped into your Telegram bot, the n8n automation takes over, automatically downloading the file, extracting the text content, and routing it to a specialized OpenAI agent. The agent is prompted to identify key fields like the invoice number, total amount, and vendor name. The result is a clean, structured analysis delivered back to the Telegram chat, drastically accelerating your accounts payable process. This powerful n8n node combination demonstrates how sophisticated AI capabilities can be seamlessly integrated into everyday messaging platforms.
This n8n workflow begins with the dedicated Telegram n8n trigger. Once a message is received:
$json.message.document). If no document is found, an error message is sent back to the chat via a Telegram n8n node.To deploy this specialized n8n workflow template, follow these steps:
Telegram Trigger: This n8n trigger initiates the entire n8n workflow whenever a message is received on the connected Telegram bot. It is the crucial starting n8n node for the automation.
Check if Document (If n8n node): Essential control flow n8n node that validates if the incoming message contains the expected file data ($json.message.document). It handles necessary error routing.
HTTP Request - Download File: A critical n8n node used to dynamically download the file contents from the Telegram API servers using the bot's access token and the file path obtained from Telegram metadata.
Extract Invoice Data (extractFromFile n8n node): This core utility n8n node specializes in reading the binary file (likely a PDF) and performing OCR or text extraction to prepare the data for the AI analysis.
OpenAI Chat Model (n8n node): Provides the necessary language model connection (e.g., using GPT-4o-mini) to the agent architecture, enabling complex reasoning and data structuring.
AI Agent - Analyze Invoice (Agent n8n node): This is where the intelligence resides. It utilizes a powerful system prompt instructing it to act as an invoice analyst, extracting structured data based on the text provided by the previous n8n node.
Format Response (Code n8n node): A custom scripting n8n node used for mapping and restructuring the data, ensuring the AI's output is cleanly packaged alongside necessary metadata (like chatId) before being sent out.
Send Analysis to Telegram (Telegram n8n node): The final action n8n node, responsible for delivering the detailed, formatted analysis back to the user via their private Telegram chat.
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Prof. Cheng Siong CHIN serves as Chair Professor in Intelligent Systems Modelling and Simulation in Newcastle University, Singapore. His academic credentials include an M.Sc. in Advanced Control and Systems Engineering from The University of Manchester and a Ph.D. in Robotics from Nanyang Technological University.







































