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Tired of manually extracting data from invoice photos sent via Telegram? One innovator has developed an AI-powered solution that leverages Gemini Vision and n8n to automate the process. The system overcomes common obstacles like poor lighting, skewed angles, and blurry text that often plague traditional Optical Character Recognition (OCR) methods.

The workflow begins with a Telegram bot receiving invoice photos. Gemini Vision API then steps in to extract structured data, including crucial fields such as invoice number, date, amount, vendor information, and line items. The extracted data is automatically formatted and validated to ensure accuracy before being pushed to Google Sheets for analysis and reporting. The entire process is seamlessly orchestrated through n8n, a workflow automation platform.

The project highlights the power of vision models in handling subpar image quality compared to conventional OCR techniques. Gemini Vision’s ability to accurately extract data even from distorted images is a key advantage. The creator emphasizes the importance of structured prompting for consistent field extraction and the necessity of incorporating validation rules to address potential edge cases.

The results demonstrate near-instant data extraction compared to manual processing, with impressive accuracy despite variations in image quality. The solution offers a scalable approach to invoice processing without requiring additional personnel. The creator of the project initially shared the concept on Reddit and is seeking feedback from others working on vision-based document extraction solutions and preferred AI models. [Reddit Post: https://old.reddit.com/r/artificial/comments/1oyqdxy/gemini_vision_n8n_for_realworld_invoice/]