💼 Case study - Automating File Processing & Renaming with AI

Last time, I shared how we automated hiring 500+ candidates for a client without an HR team. If you missed that post, check it out here.

Now, let’s talk about documents—because if you run a business, you know the struggle.

This same client receives a constant flow of receipts and invoices via email and manually saves them to Google Drive. The problem? Finding and organizing these files later is a nightmare. They needed a way to automatically process, rename, and categorize them without spending hours sorting through folders.

So we built an AI-powered automation that handles everything on autopilot. Here’s how it works:

🛠️ The Setup

1️⃣ Fetching New Files

• Every time a new email arrives with an attachment, the system downloads the file and checks if it’s a receipt or invoice.

• If it’s something else, we ignore it.

2️⃣ Smart AI Recognition

• We process the file using LlamaParse, which allows us to:

✅ Extract tables (common in invoices)

✅ Recognize logos that contain company names

✅ Parse text even from image-based PDFs (which standard N8N nodes can’t handle)

3️⃣ Context-Aware Parsing

• Instead of relying on generic AI recognition, we guide the AI with a predefined list of banks and companies the client frequently deals with.

• This makes the results far more accurate and stable.

4️⃣ File Renaming & Metadata Tagging

• AI extracts key details like date, amount, and entity name based on separate rule sets.

• Each parameter is processed separately to increase precision—because main info and entities follow different logic.

• Once identified, the file is renamed according to a structured pattern and saved in Google Drive.

5️⃣ Preventing Duplicates

• To avoid reprocessing the same document, we add hidden metadata to each file. If a document comes through again, our system detects it and skips processing.

6️⃣ Structured Data Storage

• Parsed information is saved in Airtable, where it links to related records—keeping everything structured for future reference.

✅ The Result?

• 90%+ accuracy in document recognition

• Hours saved every week—no more manual sorting

• Fully scalable—this setup works for any type of document processing

And the best part? You can adapt this workflow for any business process where file automation is needed.

🗣️ Your Turn

Do you deal with tons of files, invoices, or documents that need better organization? Could a system like this help streamline your work—or be adapted for a different process? Let me know in the comments! 🚀

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