8.Workflows: From Manual to Magical-Build AI-Powered Business Workflows with n8n

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OCR Meets AI: How Nanonets Transforms Invoices, IDs, and Receipts into Actionable Data

🧠 Introduction to Nanonets

Nanonets is an AI-driven platform that automates document processing using advanced Optical Character Recognition (OCR) and machine learning. It can extract structured data from unstructured documents like invoices, receipts, ID cards, contracts, and shipping labels — and route that data into tools like Google Sheets, QuickBooks, or your internal databases. With built-in workflow automation, human-in-the-loop approvals, and seamless integrations, Nanonets is a powerhouse for back-office efficiency.

Let’s explore five unique business automation scenarios that show how Nanonets can transform your document workflows.

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✅ Scenario 1: Extract Invoice Data and Sync with QuickBooks

Use Case: Automate accounts payable and reduce manual entry.

Steps:

1. Upload or auto-import invoices from email, Dropbox, or Google Drive.
2. Use Nanonets’ pre-trained invoice model to extract fields like vendor, amount, and due date.
3. Add a validation step for human review if confidence is low.
4. Connect QuickBooks and map extracted fields to invoice entries.
5. Export approved data directly into your accounting system.

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✅ Scenario 2: Auto-Classify Scanned Receipts and Tag by Department

Use Case: Organize expense receipts for finance and audits.

Steps:

1. Set up a workflow to watch a shared folder or email inbox for new receipts.
2. Use OCR to extract merchant, amount, and date.
3. Apply conditional logic to tag receipts by department (e.g., “Marketing” if vendor is Canva).
4. Export to Google Sheets or a finance dashboard.
5. Flag outliers (e.g., high-value or duplicate receipts) for review.

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✅ Scenario 3: Process Shipping Labels and Update Inventory in Google Sheets

Use Case: Automate logistics tracking and inventory updates.

Steps:

1. Upload scanned shipping labels from warehouse scanners.
2. Extract tracking number, SKU, and delivery status.
3. Match SKU to product database using a lookup block.
4. Update inventory levels in Google Sheets or your ERP.
5. Trigger a Slack alert if stock drops below threshold.

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✅ Scenario 4: Validate ID Documents and Flag Mismatches for Review

Use Case: Automate KYC (Know Your Customer) or employee onboarding.

Steps:

1. Upload ID documents (e.g., passports, driver’s licenses).
2. Extract name, DOB, and ID number using a custom OCR model.
3. Compare extracted data with submitted form or HR database.
4. If mismatch is detected, flag for manual review.
5. Store verified records securely in a cloud folder or database.

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✅ Scenario 5: Convert Handwritten Forms into Structured CRM Entries

Use Case: Digitize field data collection or customer intake forms.

Steps:

1. Upload scanned or photographed handwritten forms.
2. Use Nanonets’ handwriting recognition model to extract fields.
3. Clean and format data using conditional and Python blocks.
4. Push structured data into your CRM (e.g., Zoho, Salesforce).
5. Log errors or low-confidence entries for human validation.

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10. Workflows:⚡️ 5 One-Click Automations That Will Save You Hours with Integrately