Project title: AI-Powered Document Classification & Organization System Project description: Buil...Project title: AI-Powered Document Classification & Organization System Project description: Buil...
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Zakeen Khan
• Sep 7
Project title: AI-Powered Document Classification & Organization System
Project description:
Built an automated document intake and filing system in n8n that watches a Google Drive folder, reads incoming files, uses AI to figure out what each document is, extracts the relevant data, and files it into the correct folder automatically, replacing manual document sorting entirely.
The problem: The client was manually opening every new file dropped into their Drive, figuring out whether it was a contract, invoice, or general document, extracting the key details by hand, and moving it to the right folder, a slow and error-prone process as document volume grew.
What I built:
Automatic file detection and text extraction: Whenever a new document lands in Drive, the system downloads it and detects its file type (PDF, Excel, or image), then extracts the raw content using the appropriate method for that format, including AI-based text extraction for scanned images.
AI-based document classification: Extracted content is passed through a classification step that determines whether the document is a contract, an invoice, or a general document, routing it down a different path depending on its type.
Type-specific data extraction:
Contracts are processed by an AI agent (Google Gemini) that extracts structured contract data against a defined schema, prepares metadata, and moves the file into a dedicated Contracts folder
Invoices are processed by a separate AI agent (Groq) that extracts invoice-specific data, prepares metadata, and moves the file into an Invoices folder
General documents are summarized by an AI agent (OpenAI), have metadata prepared, and are archived into a general Archive folder
Centralized record keeping: Regardless of document type, every processed file's metadata is logged into a central document metadata store, giving the client a searchable record of everything that's been filed.
Outcome: The client's document intake is now fully automated end to end, new files are read, classified, and filed into the correct folder with extracted metadata, without anyone manually opening or sorting a single document.
AI Agent EngineerPrompt EngineeringGoogle GeminiN8NAI AutomationGoogle Drive
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