Document Automation FAQ: Your Questions Answered

You've heard about document automation. You've seen the promises: 95% time savings, near-zero errors, seamless integrations. But before you commit, you have questions. Real questions that marketing materials don't always address.

We get it. Adopting new technology involves risk. You're responsible for your team's productivity, your company's data, and your budget. You need straight answers, not sales pitches.

This guide answers the questions we hear most often from businesses considering document automation—honestly and completely. If you're on the fence, read this first.

The Big Picture Questions

"What exactly is document automation, and how is it different from basic OCR?"

Basic OCR (Optical Character Recognition) simply converts images of text into editable text. It's like a photocopier that produces text files instead of paper copies.

Document automation goes much further:

• Understands context: It doesn't just read text—it knows that "Invoice Total: $1,247.50" is a monetary value, not just characters
• Extracts structured data: Instead of raw text, you get organized fields (vendor name, invoice number, line items)
• Integrates with your systems: Data flows directly into your CRM, ERP, or accounting software
• Triggers workflows: Automatic approvals, notifications, and follow-up actions
• Learns and improves: Modern systems adapt to your specific document formats over time

Think of it this way: basic OCR gives you a pile of text. Document automation gives you actionable, structured data that's ready to use.

"Will this actually save us time, or will we spend all our time fixing errors?"

This is the right question to ask. Poor automation creates more work than it eliminates.

Scenario	The Manual Way	The Scanny AI Way
Processing 100 invoices	12-15 hours of data entry	15-20 minutes of review
Error rate	1-5% manual mistakes	<0.5% with validation
Time to catch errors	Days or weeks later	Immediate flagging
Scaling to 500 invoices	Hire additional staff	Same 20-minute review
Weekend processing	Overtime or delays	Automatic, 24/7
Integration effort	Manual copy-paste	Direct API sync

Real numbers: Our customers report spending 5-10 minutes daily reviewing automated extractions versus 4-6 hours doing manual entry. That's not theoretical—that's what businesses actually experience.

The key is confidence thresholds. Well-designed automation flags low-confidence extractions for human review rather than silently making mistakes. You review exceptions, not every document.

Security and Privacy Questions

"Is my data safe? Who can see our documents?"

This is non-negotiable. Your documents contain sensitive business information, customer data, and financial records. Here's what to look for:

Encryption standards:

• Data encrypted in transit (TLS 1.2+)
• Data encrypted at rest (AES-256)
• No unencrypted data storage at any point

Access controls:

• Your documents are isolated from other customers
• Role-based access within your organization
• Audit logs for every access and action

Compliance certifications:

• SOC 2 Type II (security controls)
• GDPR compliance (European data protection)
• HIPAA compliance (healthcare data)

Data retention:

• Configurable retention periods
• Automatic deletion after processing (if you choose)
• Right to delete on demand

Ask any vendor: "Where is my data stored? Who has access? How long is it retained? Can I delete it?" If they can't give you specific answers, walk away.

Scanny AI processes your documents in secure, isolated environments with enterprise-grade encryption. Your data is never used to train models or shared with third parties.

"What happens if there's a data breach?"

No system is 100% immune to security incidents. The question is: what protections are in place?

Prevention layers:

1. Infrastructure security (firewalls, intrusion detection)
2. Application security (secure coding, regular audits)
3. Access security (authentication, authorization)
4. Physical security (data center controls)

If something does happen:

• Immediate incident response protocols
• Customer notification within required timeframes
• Forensic investigation and remediation
• Insurance coverage for data breach costs

The vendors with the best security posture are the ones who talk openly about their practices—not the ones who say "trust us."

Accuracy and Reliability Questions

"How accurate is AI extraction really? What's the catch?"

Let's be honest: accuracy depends on your documents and how you set things up.

Factors that affect accuracy:

Factor	Impact	What You Can Do
Document quality	High	Use clear scans, avoid crumpled/faded docs
Document consistency	Medium	Standardize formats where possible
Field complexity	Medium	Start with simple fields, add complex ones later
Language	Low	Most platforms handle 100+ languages well
Handwriting	Medium	Expect 90-95% vs 98%+ for typed text
Schema design	High	Define fields precisely, use validation rules

Realistic accuracy expectations:

• Standard business documents (invoices, receipts): 95-99%
• Complex layouts (multi-column, tables): 90-97%
• Handwritten notes: 85-95%
• Forms with checkboxes: 92-98%

The key insight: 95% accuracy on automated processing plus human review of flagged items beats 95% accuracy on fully manual processing. Humans make mistakes too—especially on repetitive tasks.

"What happens when it makes a mistake?"

Every system makes mistakes. What matters is how you catch them and what happens next.

Built-in safeguards:

1. Confidence scoring: Each extracted field gets a confidence score. Low-confidence extractions are flagged for review.

2. Validation rules: Define business rules like "invoice total must match sum of line items" or "date cannot be in the future."

3. Human-in-the-loop: Review flagged documents in a streamlined interface. Approve, correct, or reject.

4. Learning from corrections: When you fix an error, the system learns. Similar documents are handled better next time.

Example workflow for invoice processing:

{
  "documentType": "Invoice",
  "extractionRules": {
    "fields": [
      {
        "name": "invoice_number",
        "type": "string",
        "required": true,
        "validationPattern": "^INV-[0-9]{4,}$"
      },
      {
        "name": "total_amount",
        "type": "number",
        "required": true,
        "validationRule": "must_equal_sum_of_line_items"
      },
      {
        "name": "invoice_date",
        "type": "date",
        "required": true,
        "validationRule": "not_future_date"
      },
      {
        "name": "vendor_name",
        "type": "string",
        "required": true,
        "lookupValidation": "approved_vendors_list"
      }
    ],
    "confidenceThreshold": 0.85,
    "flagForReviewWhen": "any_field_below_threshold"
  }
}

With this setup, invoices that don't match your patterns get flagged. Invoices from unknown vendors get flagged. Mismatched totals get flagged. You review exceptions—not every single document.

Integration Questions

"Will this work with our existing systems?"

This is where many automation projects fail. The extraction works great, but getting data into your actual systems becomes a nightmare.

Questions to ask:

1. What integrations are available out-of-the-box?

   • CRMs (Salesforce, HubSpot, Zoho)
   • ERPs (SAP, Oracle, NetSuite)
   • Accounting (QuickBooks, Xero, FreshBooks)
   • Cloud storage (Google Drive, Dropbox, OneDrive, SharePoint)
   • Email providers (Gmail, Outlook)

2. Is there an API for custom integrations?

   • REST API with clear documentation
   • Webhook support for real-time updates
   • Bulk operations for high-volume processing

3. Can you trigger workflows in other tools?

   • Zapier/Make integration
   • Native workflow actions
   • Custom webhook destinations

Scanny AI integration approach:

We built the platform assuming you have existing tools. That's why we offer:

• Pre-built connectors for major business platforms
• Webhook actions that fire when processing completes
• Full REST API for custom integrations
• No-code workflow builder for common scenarios

"How hard is the initial setup?"

Implementation complexity ranges from "30-minute self-service" to "multi-month enterprise project." Where you fall depends on:

Simple setup (hours, not days):

• Standard document types (invoices, receipts, forms)
• Cloud storage integration (Google Drive, Dropbox)
• Sending data to spreadsheets or simple webhooks
• No custom validation requirements

Moderate setup (days to weeks):

• Custom document schemas with specific fields
• ERP or accounting system integration
• Approval workflows with routing logic
• Team training and change management

Complex setup (weeks to months):

• High-volume enterprise deployment
• Custom on-premise integration requirements
• Regulatory compliance validation
• Multi-department rollout with different workflows

Our recommendation: Start with a simple pilot. Automate one document type, prove the value, then expand. Don't try to boil the ocean on day one.

Cost and ROI Questions

"How much does this actually cost?"

Document automation pricing typically falls into these models:

Pricing Model	How It Works	Best For
Per-document	Pay for each document processed	Variable volume, testing
Monthly subscription	Fixed price for quota	Predictable volume
Tiered usage	Price decreases at higher volumes	Growing businesses
Enterprise	Custom pricing for large deployments	High-volume, complex needs

Cost factors to consider:

• Base processing cost per document
• Integration fees (if any)
• Storage costs for archived documents
• Support level (self-service vs. dedicated)
• Training and implementation (often one-time)

Hidden costs to watch for:

• Overage charges at unpredictable rates
• Per-user licensing that limits adoption
• Integration connectors priced separately
• Minimum commitments that don't match your volume

"What's the actual ROI? Show me the math."

Let's do the calculation with realistic numbers.

Scenario: A business processes 500 invoices per month manually.

Current costs (manual processing):

Cost Item	Calculation	Monthly Cost
Data entry labor	500 invoices × 8 min × ($25/hr)	$1,667
Error correction	3% error rate × 15 min fix time	$94
Late payment penalties	2% of invoices × $50 avg penalty	$500
Filing and retrieval	2 hours/week × $25/hr	$200
Total Manual Cost		$2,461/month

With Scanny AI automation:

Cost Item	Calculation	Monthly Cost
Processing subscription	500 documents/month plan	$149
Review time	500 invoices × 30 sec review	$104
Exception handling	5% flagged × 3 min each	$31
Total Automated Cost		$284/month

Monthly savings: $2,177 Annual savings: $26,124 ROI: 766%

Beyond the numbers: These calculations don't include the value of faster payments (due to quicker processing), reduced audit risk (from better accuracy), or employee satisfaction (from eliminating tedious work).

"How long until we see results?"

Most businesses see measurable results within the first month:

Week 1: Setup, schema definition, initial testing Week 2: First production documents processed, review workflow established Week 3: Team comfortable with review process, volume ramping up Week 4: Full production volume, first month metrics available

By month three, you should have clear data on:

• Time saved per document
• Error rate comparison
• Integration reliability
• Team adoption and satisfaction

Implementation Questions

"Do we need technical expertise to set this up?"

For most use cases, no. Modern document automation platforms are designed for business users, not developers.

What you can do without coding:

• Create document schemas using visual builders
• Set up cloud storage integrations (connect your Google Drive in clicks)
• Define validation rules using dropdown menus
• Build approval workflows with drag-and-drop
• Configure notifications and alerts
• View dashboards and reports

When you might need technical help:

• Custom ERP integrations with legacy systems
• Complex validation logic (multi-step calculations)
• High-volume API integrations
• On-premise deployment requirements
• Custom security configurations

Scanny AI approach: Our platform is no-code by default. You can define custom schemas, set up workflows, and connect integrations without writing a single line of code. For advanced needs, we offer a full REST API that your development team can use.

"What if we get stuck? What support is available?"

Support quality varies wildly across vendors. Ask specifically:

Self-service resources:

• Documentation quality and completeness
• Video tutorials for common tasks
• Community forums or knowledge base
• Template library for common document types

Direct support:

• Response time guarantees (SLA)
• Support channels (chat, email, phone)
• Support hours (business hours vs. 24/7)
• Dedicated account manager (for enterprise)

Implementation help:

• Onboarding assistance included or paid
• Training sessions for your team
• Custom schema setup help
• Integration consulting

Red flag: If a vendor won't let you talk to support before you buy, that tells you something about their confidence in their support quality.

The Questions Nobody Asks (But Should)

"What happens if we want to leave?"

Vendor lock-in is a real concern. Make sure you understand:

Data portability:

• Can you export all your documents?
• Can you export all extracted data?
• What format will exports be in?
• Is there an export fee?

Contract terms:

• What's the minimum commitment period?
• What are the cancellation terms?
• Are there early termination penalties?
• What happens to your data after cancellation?

Migration path:

• How would you move to a different vendor?
• Can you export your schemas and configurations?
• Is there a transition period for moving data?

"How does this scale as we grow?"

Start with your current needs, but think ahead:

Volume scaling:

• What happens when you 10x your document volume?
• Are there volume discounts at higher tiers?
• Is there a maximum processing capacity?

Feature scaling:

• Can you add more document types easily?
• Can you add more integrations later?
• Can you add more team members?

Geographic scaling:

• Does the platform support multiple regions?
• Can you handle documents in different languages?
• Are there data residency options?

"What's the vendor's roadmap?"

You're not just buying today's product—you're betting on tomorrow's improvements:

• How often are new features released?
• What's on the public roadmap?
• How do they handle customer feature requests?
• What's their funding/stability situation?
• How long have they been in business?

A platform that's actively developing and improving will serve you better long-term than one that's in maintenance mode.

Making Your Decision

After reading all these questions, you might feel overwhelmed. Here's how to simplify your decision:

Start With Your Pain Point

What document process is causing the most frustration right now? Start there. Don't try to automate everything at once.

Test With Real Documents

Any vendor worth considering will let you test with your actual documents—not just demo data. Run a pilot with 50-100 real documents before committing.

Calculate Your Specific ROI

Use the formula above with your actual numbers. If the math doesn't work for your volume, automation might not be the right choice yet.

Talk to Existing Customers

Ask for references in your industry. What was their implementation experience? What challenges did they face? Would they choose the same vendor again?

Trust Your Instincts

If something feels off—pushy sales tactics, vague answers, unclear pricing—trust that feeling. There are plenty of good options out there.

Ready to Get Your Questions Answered?

You've done your research. You understand what document automation can and can't do. You know the right questions to ask.

The next step is simple: Try it yourself.

Start your free trial with Scanny AI. Upload your documents, define your schema, and see the results in seconds. No credit card required. No commitment. Just answers.

Already have an account? Log in and start automating your first workflow.

Still have questions? We're here to help. Not with a sales pitch—with honest answers about whether Scanny AI is the right fit for your specific needs. Sometimes the answer is no, and we'll tell you that. Let's figure it out together.