AI-powered invoice extractor via Telegram to Airtable
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Important notice
This workflow is provided as-is. Please review and test before using in production.
Overview
๐ Description
This workflow automates the extraction of structured invoice data from PDF files sent via Telegram and stores it in Airtable. It leverages GPT-4o for intelligent parsing and includes conversational memory for a seamless user experience. Designed for businesses and freelancers who receive invoices digitally and want to streamline their record-keeping.
โ๏ธ How It Works
- Telegram Trigger โ Listens for incoming messages and PDF attachments.
- Switch Node โ Filters messages to ensure only PDFs are processed.
- Extract from File โ Parses the PDF content for text extraction.
- Edit Fields โ Prepares the extracted data for AI processing.
- AI Agent (GPT-4o) โ Orchestrates the workflow, prompts the user for missing info, and extracts structured data.
- Simple Memory โ Maintains conversational context across sessions.
- Create Invoice (Airtable Tool) โ Creates a new invoice record in Airtable.
- Create Line Item (Airtable Tool) โ Adds individual line items linked to the invoice.
- Telegram Response โ Sends confirmation back to the user.
๐ Required Credentials
To run this workflow successfully, youโll need:
- Telegram Bot Token (via @BotFather)
- OpenAI API Key (with GPT-4o access)
- Airtable API Key and access to:
- Base:
Invoice Tracker Proper - Tables:
InvoicesandLine Items
- Base:
๐งฐ Airtable Structure
Invoices Table Fields:
- Invoice Number
- Date
- Supplier
- Supplier Address
- Tax ID
- PO Number
- Due Date
- Receiver Name
- Receiver Address
- Delivery Date
- Total Tax
- Total Amount
Line Items Table Fields:
- Product Code
- Description
- Unit Price
- Quantity
- Unit Type
- Sub Total
- Invoice (linked)
๐ง Features
- AI-powered invoice parsing
- PDF text extraction
- Airtable record creation with relational linking
- Telegram-based user interaction
- Conversational memory
- Error handling and data validation