10 Documents You Can Automate Beyond Invoices

When most people think about document automation, invoices immediately come to mind. And for good reason—invoice processing is one of the most tedious, error-prone tasks plaguing finance teams worldwide. But here's what most businesses don't realize: invoices are just the tip of the iceberg.

Your organization handles dozens of different document types every single day. Resumes. Purchase orders. Shipping labels. Contracts. ID cards. Insurance claims. And your team is probably still processing most of them manually.

The average knowledge worker spends 2.5 hours per day searching for information in documents. That's 31% of their workday. What if you could reclaim that time?

In this comprehensive guide, we'll explore 10 critical document types beyond invoices that you can automate right now using intelligent OCR and AI-powered extraction. For each document type, you'll see exactly what data to extract, how to structure it, and what workflows to build.

Why Automate Documents? The Manual Way vs. The Scanny AI Way

Let's be brutally honest about what manual document processing costs your business:

Metric	The Manual Way	The Scanny AI Way
Processing Time	5-15 minutes per document	5-30 seconds per document
Error Rate	3-5% (human data entry errors)	<0.5% (AI-validated extraction)
Cost Per Document	$5-$25 (labor + error correction)	$0.10-$0.50 (automated processing)
Scalability	Hire more staff = linear cost increase	Process 10x more documents = same cost
Integration	Manual copy-paste into systems	Automatic push to CRM/ERP/ATS
Searchability	Email attachments = lost forever	Structured JSON = instant search
Compliance & Audit	Manual filing, prone to loss	Automatic logging with full traceability

The math is simple: Manual processing doesn't scale. Automation does.

The 10 Document Types You Should Automate Today

1. Resumes & CVs (Recruiting Automation)

Use Case: HR teams processing 100+ applications per job posting

If you're in recruiting, you know the pain: opening each PDF resume, manually copying candidate information into your ATS, trying to parse dates and job titles while fighting inconsistent formatting.

What to Extract:

• Personal information (name, email, phone, location)
• Work experience (companies, positions, dates, descriptions)
• Education (degrees, institutions, graduation dates)
• Skills and certifications
• Languages and proficiency levels

Scanny AI JSON Schema for Resumes:

{
  "documentType": "resume",
  "fields": [
    {"name": "fullName", "type": "string"},
    {"name": "email", "type": "string"},
    {"name": "phone", "type": "string"},
    {"name": "location", "type": "string"},
    {"name": "linkedInUrl", "type": "string"},
    {"name": "summary", "type": "text"},
    {
      "name": "workExperience",
      "type": "array",
      "fields": [
        {"name": "company", "type": "string"},
        {"name": "position", "type": "string"},
        {"name": "startDate", "type": "date"},
        {"name": "endDate", "type": "date"},
        {"name": "description", "type": "text"},
        {"name": "location", "type": "string"}
      ]
    },
    {
      "name": "education",
      "type": "array",
      "fields": [
        {"name": "institution", "type": "string"},
        {"name": "degree", "type": "string"},
        {"name": "fieldOfStudy", "type": "string"},
        {"name": "graduationDate", "type": "date"},
        {"name": "gpa", "type": "number"}
      ]
    },
    {"name": "skills", "type": "array"},
    {"name": "certifications", "type": "array"},
    {"name": "languages", "type": "array"}
  ]
}

Workflow: Email attachment → Scanny AI extraction → Automatic ATS update → Candidate ranking → Interview scheduling trigger

2. Purchase Orders (Procurement Automation)

Use Case: Procurement teams managing supplier orders and inventory

Purchase orders are the backbone of supply chain operations. Every PO that sits in someone's email inbox is a delayed shipment, a confused supplier, and a potential stockout.

What to Extract:

• PO number and date
• Supplier details (name, address, contact)
• Buyer details
• Line items (product codes, descriptions, quantities, unit prices)
• Total amounts (subtotal, tax, shipping, total)
• Delivery date and shipping address
• Payment terms

Workflow: Supplier sends PO → Scanny AI extraction → ERP system update → Inventory reservation → Fulfillment notification → Shipment tracking

3. Receipts & Expense Reports (Finance Automation)

Use Case: Finance teams processing employee expense claims

Every business traveler knows the drill: collect receipts, photograph them, manually enter them into an expense system, submit for approval, wait. Repeat 20 times per trip.

What to Extract:

• Merchant name and location
• Transaction date and time
• Receipt number
• Line items and quantities
• Subtotal, tax, tip, and total
• Payment method
• Currency

Scanny AI JSON Schema for Receipts:

{
  "documentType": "receipt",
  "fields": [
    {"name": "merchantName", "type": "string"},
    {"name": "merchantAddress", "type": "string"},
    {"name": "merchantPhone", "type": "string"},
    {"name": "transactionDate", "type": "date"},
    {"name": "transactionTime", "type": "time"},
    {"name": "receiptNumber", "type": "string"},
    {
      "name": "items",
      "type": "array",
      "fields": [
        {"name": "description", "type": "string"},
        {"name": "quantity", "type": "number"},
        {"name": "unitPrice", "type": "number"},
        {"name": "totalPrice", "type": "number"}
      ]
    },
    {"name": "subtotal", "type": "number"},
    {"name": "tax", "type": "number"},
    {"name": "tip", "type": "number"},
    {"name": "total", "type": "number"},
    {"name": "paymentMethod", "type": "string"},
    {"name": "currency", "type": "string"},
    {"name": "category", "type": "string"}
  ]
}

Workflow: Employee snaps photo → Scanny AI extraction → Expense management system → Manager approval → Accounting reconciliation → Reimbursement

4. Contracts & Agreements (Legal Automation)

Use Case: Legal teams managing hundreds of vendor, client, and employment contracts

Contracts are goldmines of critical information—but only if you can find what you need. Most companies have contracts scattered across email, shared drives, and filing cabinets.

What to Extract:

• Contract parties (names, addresses, roles)
• Contract type (NDA, MSA, employment, etc.)
• Effective date and expiration date
• Renewal terms and notice periods
• Financial terms (fees, payment schedule)
• Key obligations and deliverables
• Termination clauses
• Liability caps and indemnification
• Governing law and jurisdiction

Workflow: Signed contract received → Scanny AI extraction → Contract management system → Calendar reminders for renewals → Compliance dashboard → Automated renewal workflows

5. Identity Documents (KYC & Onboarding Automation)

Use Case: Banks, insurance companies, and regulated industries handling customer onboarding

Know Your Customer (KYC) compliance requires collecting and verifying ID documents. Manual verification is slow, inconsistent, and vulnerable to fraud.

What to Extract:

• Document type (passport, driver's license, national ID)
• Full name
• Date of birth
• Document number
• Issue date and expiration date
• Nationality/Country of issue
• Address (if present)
• Photo extraction for facial recognition

Workflow: Customer uploads ID → Scanny AI extraction + validation → Identity verification system → Fraud detection checks → Automatic account approval → Compliance logging

Security Note: ID document processing requires special handling. Scanny AI supports secure processing with encryption at rest and in transit, plus automatic PII redaction for compliance with GDPR, CCPA, and other regulations.

6. Shipping Labels & Bills of Lading (Logistics Automation)

Use Case: Logistics and fulfillment teams tracking shipments

Every package that enters your warehouse has a shipping label. Every shipment you send has tracking information. Manually entering this data creates bottlenecks and tracking errors.

What to Extract:

• Tracking number
• Carrier and service type
• Sender details (name, address)
• Recipient details (name, address)
• Package dimensions and weight
• Shipment date and expected delivery
• Barcode data

Workflow: Package arrives → Scanny AI extraction from label → WMS system update → Inventory receiving → Customer notification → Real-time tracking dashboard

7. Medical Records & Lab Reports (Healthcare Automation)

Use Case: Healthcare providers, insurance companies, and medical billing departments

Medical documents contain critical patient information that needs to be accessible instantly—not buried in scanned PDFs.

What to Extract:

• Patient demographics (name, DOB, MRN)
• Provider information
• Visit date and type
• Diagnosis codes (ICD-10)
• Procedure codes (CPT)
• Prescribed medications and dosages
• Lab results (test names, values, reference ranges)
• Vital signs

Workflow: Lab report received → Scanny AI extraction → EHR system update → Doctor notification → Patient portal update → Billing system integration

8. Insurance Claims (Claims Processing Automation)

Use Case: Insurance companies processing thousands of claims daily

Insurance claims combine document processing with complex decision-making. The faster you can extract and validate claim information, the faster you can pay out (or deny) claims.

What to Extract:

• Claim number and date
• Policy number and type
• Claimant information
• Incident date and location
• Incident description
• Damage assessment
• Supporting documents (police reports, medical bills, photos)
• Claimed amount

Scanny AI JSON Schema for Insurance Claims:

{
  "documentType": "insuranceClaim",
  "fields": [
    {"name": "claimNumber", "type": "string"},
    {"name": "claimDate", "type": "date"},
    {"name": "policyNumber", "type": "string"},
    {"name": "policyType", "type": "string"},
    {"name": "claimantName", "type": "string"},
    {"name": "claimantContact", "type": "string"},
    {"name": "incidentDate", "type": "date"},
    {"name": "incidentLocation", "type": "string"},
    {"name": "incidentDescription", "type": "text"},
    {"name": "damageType", "type": "string"},
    {"name": "estimatedDamage", "type": "number"},
    {"name": "claimedAmount", "type": "number"},
    {"name": "supportingDocuments", "type": "array"},
    {"name": "witnessInformation", "type": "text"},
    {"name": "policeReportNumber", "type": "string"}
  ]
}

Workflow: Claim submitted → Scanny AI extraction from all attachments → Claims management system → Fraud detection analysis → Adjuster assignment → Automatic approval (if under threshold) → Payment processing

9. Bank Statements (Financial Reconciliation Automation)

Use Case: Accounting teams reconciling transactions and auditors reviewing financial records

Bank statements are still surprisingly manual in many organizations. Accountants download PDFs, manually enter transactions, and reconcile against internal records.

What to Extract:

• Account holder name and account number
• Statement period (start and end dates)
• Opening and closing balances
• Transaction list (date, description, debit/credit, balance)
• Fees and charges
• Interest earned

Workflow: Bank statement received → Scanny AI extraction → Accounting software import → Automatic reconciliation → Exception flagging → Audit trail creation

10. Certificates & Licenses (Compliance & Credential Verification)

Use Case: HR departments, contractors, and regulated industries managing certifications

Professional licenses, safety certifications, and training credentials have expiration dates. Miss one, and you could face fines, project delays, or liability issues.

What to Extract:

• Certificate/License type
• Holder name
• Certificate number
• Issuing authority
• Issue date and expiration date
• Scope of certification
• Training hours or credits

Workflow: Employee submits certificate → Scanny AI extraction → HR system update → Calendar reminder set for renewal → Compliance dashboard update → Automatic alerts 90/60/30 days before expiration

How Scanny AI Processes These Documents: The Technical Workflow

Now that you've seen what's possible, let's talk about how it actually works. Understanding the technical workflow will help you implement automation in your own organization.

Step 1: Document Ingestion (Multiple Input Methods)

Scanny AI accepts documents through multiple channels:

• Email forwarding: Forward documents to your unique Scanny email address
• API upload: Programmatic upload via REST API
• Integration connectors: Direct integration with Google Drive, Dropbox, SharePoint, Gmail, and more
• Manual upload: Web interface for ad-hoc processing

Step 2: AI-Powered OCR Processing

Scanny uses Google Gemini Vision API for state-of-the-art document understanding:

• Multi-modal processing: Understands text, tables, layouts, and even handwriting
• Context-aware extraction: Doesn't just read text—understands what it means
• Multi-language support: Processes documents in 100+ languages
• Complex layout handling: Handles multi-column layouts, forms, and nested tables

Step 3: Structured Data Extraction

This is where the magic happens. Instead of giving you unstructured text, Scanny returns structured JSON based on your custom schema:

{
  "success": true,
  "documentType": "resume",
  "extractedData": {
    "fullName": "Sarah Johnson",
    "email": "sarah.johnson@email.com",
    "phone": "+1-555-0123",
    "workExperience": [
      {
        "company": "Tech Corp",
        "position": "Senior Software Engineer",
        "startDate": "2020-03-01",
        "endDate": "2024-12-01",
        "description": "Led development of cloud infrastructure..."
      }
    ],
    "skills": ["Python", "AWS", "Docker", "Kubernetes"],
    "education": [
      {
        "institution": "State University",
        "degree": "BS Computer Science",
        "graduationDate": "2019-05-15"
      }
    ]
  },
  "confidence": 0.97,
  "processingTime": "2.3s"
}

Step 4: Validation & Quality Control

Before pushing data to your systems, Scanny validates:

• Schema compliance: Ensures all required fields are present
• Data type validation: Verifies numbers are numbers, dates are dates, etc.
• Business rule checks: Custom validation rules (e.g., "total must equal sum of line items")
• Confidence scoring: Flags low-confidence extractions for human review

Step 5: Integration & Workflow Automation

The extracted data automatically flows into your existing systems:

• CRM integration: Salesforce, HubSpot, Pipedrive, Zoho
• ERP integration: NetSuite, SAP, Oracle, QuickBooks
• ATS integration: Greenhouse, Lever, Workday
• Custom webhooks: Send data to any system via HTTP POST
• Zapier/Make.com: Connect to 5,000+ apps with no-code integrations

Step 6: Analytics & Continuous Improvement

Scanny doesn't just process documents—it learns from them:

• Processing analytics: Track volume, success rates, and processing times
• Cost tracking: Monitor per-document costs and ROI
• Error analysis: Identify common extraction errors and improve schemas
• Usage patterns: Understand which document types you process most

Getting Started: Your First Automated Document Workflow

Ready to stop drowning in documents? Here's how to get started with Scanny AI in under 10 minutes:

1. Sign Up & Choose Your First Document Type

Start your free trial and select one document type from this list to automate first. We recommend starting with receipts or resumes—they're high-volume and deliver immediate ROI.

2. Define Your JSON Schema

Use our visual schema builder or write your own JSON schema. Start simple—you can always add more fields later.

3. Process Your First 10 Documents

Upload a batch of sample documents and review the extracted data. Adjust your schema based on results.

4. Connect Your Integration

Link Scanny to your CRM, ERP, or ATS. Or use our webhook to send data to any custom system.

5. Automate the Input

Set up email forwarding, API upload, or Google Drive monitoring so documents automatically flow into Scanny.

6. Monitor & Optimize

Use the Scanny dashboard to track processing volume, accuracy, and cost. Continuously improve your schemas based on real-world results.

Real-World Impact: What Customers Are Saying

"We were processing 200+ resumes per week manually. Each one took 10-15 minutes to enter into our ATS. Scanny cut that to 30 seconds per resume. We saved 40+ hours per week." — Recruitment Manager, Tech Startup

"Our AP team was drowning in invoices, receipts, and purchase orders. Scanny automated 90% of our document processing. We reduced our processing cost per document from $12 to $0.50." — CFO, Mid-Size Retailer

"Contract renewals were a nightmare. We had no centralized system and missed critical renewal dates. Scanny extracts all key dates and terms, then pushes them to our contract management system. We haven't missed a renewal since." — General Counsel, Professional Services Firm

The Future of Document Processing Is Here

Manual document processing is a relic of the past. Every hour your team spends copying data from documents is an hour they're not spending on strategic work that actually moves your business forward.

The technology exists today to automate virtually any document type. The question isn't "Can I automate this?"—it's "Why am I still doing this manually?"

Start with one document type. Prove the ROI. Then expand. Within 6 months, you could have 10+ document workflows fully automated, saving thousands of hours and tens of thousands of dollars.

Ready to Automate Your Documents?

Stop wasting time on manual data entry. Start extracting structured data from any document type in seconds.

Start your free trial today and process your first 100 documents free. No credit card required.

Already convinced? Log in and start building your first workflow.

Have questions about which documents to automate first? Contact our team and we'll help you identify the highest-ROI opportunities for your business.

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About Scanny AI: Scanny is an intelligent document processing platform that extracts structured data from any document type using advanced OCR and AI. Built for developers and business teams, Scanny integrates seamlessly with your existing tools and workflows. Learn more at Scanny AI.