What This Workflow Does
What This Workflow Does Upload a document (PDF, PNG, JPEG) via a web form and let an AI agent classify it and route it to the correct Google Drive folder on its own. No rule-based routing, no Switch nodes – the agent decides the category and calls the matching move tool. Documents it can't confidently classify are moved to a Needs Review folder and flagged via Slack. How It Works User uploads a file through the hosted web form The file is uploaded to a temporary Incoming folder in Google Drive The file ID and name are passed to the AI Agent The agent classifies the document and calls the matching Move tool (e.g. move_to_medical) If it can't confidently classify, it calls Move to Needs Review + sends a Slack alert Supported categories: medical_invoice · restaurant_invoice · hotel_invoice · trades_invoice · telecom_invoice Setup Guide 1. Create Your Google Drive Folders Create one folder per category in Google Drive: Incoming** (temporary landing folder) Medical* · *Restaurant* · *Hotel* · *Trades* · *Telecom** Needs Review** 2. Connect Google Drive In n8n, go to Settings → Credentials and create a Google Drive OAuth2 credential This requires a Client ID and Client Secret from Google Cloud Console (APIs & Services → Credentials → OAuth 2.0 Client ID) Make sure the Google Drive API is enabled in your Google Cloud project Open the Upload to Incoming Folder node and select your Incoming folder Open each of the 6 Move tool nodes and select the correct target folder 3. Connect Your Chat Model Add a credential for your chosen model (Gemini, OpenAI, Anthropic) in Settings → Credentials Open the Chat Model node and assign the credential Any tool-calling capable model will work – Gemini 1.5 Pro or GPT-4o recommended 4. Connect Slack Create a Slack API credential in n8n (needs a Bot Token with chat:write scope) Create a channel for review notifications (e.g. #document-review) Invite the bot to that channel Open the Slack: Notify Review Channel node and select the correct channel 5. Activate & Test Click Active in the top-right corner of n8n Open the form URL and upload a test document Check the execution log to confirm the classification and the move action Verify the file lands in the correct Google Drive folder Test with an unrecognizable document to confirm the Slack alert fires Notes The agent's classification quality depends on the filename and the chat model's reasoning. Descriptive filenames improve accuracy significantly. This workflow is an agentic demo – it replaces deterministic routing with LLM decision-making. For production-grade document classification with structured extraction, per-field prompting, and explicit confidence scoring, check out the easybits Extractor community node. An n8n automation workflow template by Felix.
Felix
web
free
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