Privacy-First Document AI: What to Look For

AI document tools are incredibly useful. They're also processing your most sensitive information.

Contracts. Financial reports. Legal documents. Medical records. Research data.

Before uploading anything confidential, you need to understand how your data is handled. Here's a guide to evaluating privacy and security in document AI.

The Privacy Trade-Off

Every AI document tool faces a fundamental tension:

• Usefulness requires processing your document content
• Privacy requires protecting that content

There's no magic solution. But some tools handle this better than others.

Key Security Questions

Before choosing a document AI tool, ask these questions:

1. Where is my data stored?

What to look for:

• Clear disclosure of data center locations
• Encryption at rest (data is encrypted when stored)
• Geographic options (EU data residency for GDPR)
• Named cloud providers (AWS, GCP, Azure have strong security)

Red flags:

• Vague language about data storage
• No mention of encryption
• Unclear data retention policies

2. How is my data transmitted?

What to look for:

• HTTPS/TLS encryption for all connections
• No data sent over unencrypted channels
• Certificate transparency

How to verify:

• Check for HTTPS in the browser
• Look for TLS 1.2 or 1.3 mentioned in security docs

3. Who can access my documents?

What to look for:

• Clear access controls documentation
• Role-based access for enterprise plans
• Audit logs (for business/enterprise tiers)
• No employee access without consent

Red flags:

• Unclear employee access policies
• No access logs available
• Shared document storage without isolation

4. Is my data used for AI training?

This is critical. Many AI tools use customer data to train models.

What to look for:

• Explicit statement: "Your data is not used to train AI models"
• Opt-out mechanisms if training does occur
• Distinction between free and paid tiers (free often has fewer protections)

Red flags:

• No mention of training data practices
• Buried clauses allowing training use
• Different policies for different tiers

5. How long is my data retained?

What to look for:

• Clear retention periods stated
• Ability to delete data immediately
• Confirmation that deleted data is truly removed
• Backup and replica handling explained

Best practices:

• 30 days or less for auto-deletion
• User-controllable deletion
• Cryptographic erasure for backups

6. What compliance certifications exist?

Certifications indicate independent verification of security practices.

Common certifications:

• SOC 2 Type II - Most relevant for SaaS, covers security/availability/confidentiality
• ISO 27001 - Information security management
• GDPR compliance - European data protection (required for EU users)
• HIPAA - Healthcare data (critical for medical documents)
• PCI DSS - Payment card data (if payments are involved)

What to verify:

• Ask to see actual certification reports (under NDA if needed)
• Check certification dates (they expire)
• Understand what's covered vs. what's not

Understanding AI Processing

Document AI tools typically use large language models (LLMs) for processing. Understanding the processing chain helps evaluate privacy:

Processing Options

API-based processing:

• Your document is sent to an external AI provider (like OpenAI or Google)
• The AI provider has access to your content
• Look for business agreements that restrict AI provider usage

Self-hosted models:

• Processing happens on the tool's own infrastructure
• No external AI provider sees your data
• Potentially less capable but more private

On-device processing:

• Processing happens on your device
• Most private but currently limited capability
• Emerging option for the future

Most document AI tools use API-based processing with external AI providers. This means your data is transmitted to (and processed by) the AI provider.

What to ask about AI providers

• Which LLM providers are used?
• Do they have enterprise/API agreements that prevent training?
• Is data logged by the AI provider?
• What are the AI provider's data practices?

Privacy Features to Look For

User Controls

Essential:

• Delete individual documents
• Delete entire account and all data
• Export your data
• View what data is stored

Nice to have:

• Set document expiration dates
• View access logs
• Control sharing permissions

Enterprise Features

For business use:

• Single sign-on (SSO)
• Admin controls for user access
• Audit logs
• Data residency options
• Custom retention policies

Technical Measures

• End-to-end encryption (rare but ideal)
• Zero-knowledge architecture (provider can't read your data)
• Client-side encryption before upload
• Secure key management

Document Sensitivity Levels

Not all documents need the same protection. Consider a tiered approach:

High Sensitivity

• Legal contracts
• Medical records
• Financial statements
• Personal identification documents
• Proprietary business information

Recommendation: Only use tools with strong security posture, SOC 2 certification, and clear privacy policies. Consider enterprise tiers.

Medium Sensitivity

• Internal business reports
• Research papers (pre-publication)
• Meeting notes
• Project documentation

Recommendation: Use reputable tools with clear privacy policies. Free tiers may be acceptable for non-critical items.

Low Sensitivity

• Published papers
• Public reports
• General reference documents
• Non-confidential personal documents

Recommendation: Convenience can be prioritized. Most reputable tools are fine.

Red Flags to Avoid

In Privacy Policies

• "We may share data with third parties for any purpose"
• "By using our service, you grant us a license to use your content"
• No mention of data deletion rights
• Policies that apply to "aggregated" or "anonymized" data (often a loophole)

In Practice

• No HTTPS on the main site
• No clear security documentation
• Inability to delete your data
• No response to security questions
• Free tool with no apparent business model (you might be the product)

In Communication

• Evasive answers to security questions
• No security contact or responsible disclosure policy
• Claims of "military-grade encryption" without details (marketing speak)

How TalkTheDoc Handles Privacy

Full transparency on our approach:

Data Processing

• Documents are processed using industry-standard AI providers (OpenAI, Google) with enterprise agreements
• Enterprise API agreements prevent training on customer data
• All processing uses encrypted connections

Data Storage

• Documents stored on Convex cloud infrastructure
• Encryption at rest and in transit
• Data isolated per user account

Data Retention

• Users can delete documents at any time
• Deleted documents are removed from active storage
• Account deletion removes all user data

What We Don't Do

• We don't use your documents to train AI models
• We don't sell your data to third parties
• We don't access your documents without consent

Security Features

• TLS encryption on all connections
• Authentication via Clerk (SOC 2 certified)
• Webhook verification prevents spoofed requests
• Rate limiting prevents abuse

Making the Decision

When evaluating document AI tools for sensitive documents:

1. Read the privacy policy - Not the marketing, the actual policy
2. Check for certifications - SOC 2 Type II is the minimum for business use
3. Ask about AI training - Get explicit confirmation your data isn't used
4. Test deletion - Upload a test document, delete it, verify it's gone
5. Consider the business model - Free tools often monetize data

For truly sensitive documents, consider whether AI processing is necessary at all. Sometimes the old-fashioned way is appropriate.

The Future of Private Document AI

The industry is moving toward more private options:

• On-device models becoming more capable
• Confidential computing for cloud processing without exposure
• Zero-knowledge architectures gaining traction
• Privacy regulations forcing better practices

Today's best practices will become table stakes. Choose tools that are already ahead of the curve.

Summary

Uploading documents to AI tools involves trust. That trust should be verified, not assumed.

Before using any document AI:

1. Know where your data goes
2. Understand who can access it
3. Confirm it's not used for training
4. Verify you can delete it
5. Match tool security to document sensitivity

Your documents contain valuable information. Make sure they're treated with the care they deserve.