Enterprise Security Features Checklist
Data Encryption
- ✅ 256-bit AES encryption at rest
- ✅ TLS 1.2/1.3 encryption in transit
- ✅ End-to-end encryption options
- ✅ Secure key management
- ✅ Private storage locations (Enterprise)
Access Controls
- ✅ Single Sign-On (SSO) integration
- ✅ Multi-Factor Authentication (MFA)
- ✅ Role-Based Access Control (RBAC)
- ✅ Super Admin workspace controls
- ✅ Granular permission settings
Data Management
- ✅ Custom data retention policies
- ✅ 0-day retention options (no AI training)
- ✅ Data deletion on demand
- ✅ Meeting recording pause/redact
- ✅ Department exclusion rules
Monitoring & Compliance
- ✅ Comprehensive audit trails
- ✅ Real-time activity monitoring
- ✅ Automated compliance reporting
- ✅ Security incident alerts
- ✅ Regular penetration testing
Compliance Certifications Explained
SOC2 Type II
SOC2 Type II is the gold standard for cloud security, requiring a 6+ month audit of security controls. It demonstrates that a vendor has implemented and maintains robust security practices over time, not just at a single point.
What It Covers:
- • Security controls and policies
- • Availability and system uptime
- • Processing integrity
- • Confidentiality of data
- • Privacy protections
Compliant Tools:
HIPAA Compliance
HIPAA compliance is essential for healthcare organizations. It requires specific safeguards for Protected Health Information (PHI), including encryption, access controls, and audit trails. Vendors must sign a Business Associate Agreement (BAA).
Key Requirements:
- • PHI encryption (AES-256)
- • Business Associate Agreement (BAA)
- • Access controls and audit trails
- • Staff security training
- • Incident response procedures
HIPAA-Ready Tools:
- • Fireflies.ai (Enterprise)
- • Sembly AI
- • Fellow
- • Read.ai
GDPR Compliance
GDPR is mandatory for processing EU residents' data. It requires explicit consent, data minimization, right to deletion, and data portability. Cross-border transfers need Standard Contractual Clauses (SCCs).
Key Requirements:
- • Explicit consent for recording
- • Right to access and deletion
- • Data Processing Agreements
- • 30-day response to requests
- • Privacy by design
GDPR-Compliant Tools:
- • Most major meeting AI tools
- • Fireflies.ai
- • Sembly AI
- • tl;dv
Enterprise Security Comparison by Vendor
| Feature | Fireflies.ai | Sembly AI | Fellow | Otter.ai |
|---|---|---|---|---|
| SOC2 Type II | ✓ | ✓ | ✓ | ✓ |
| HIPAA BAA | Enterprise | ✓ | ✓ | Enterprise |
| GDPR | ✓ | ✓ | ✓ | ✓ |
| SSO/SAML | ✓ | ✓ | ✓ | Enterprise |
| AES-256 Encryption | ✓ | ✓ | ✓ | ✓ |
| Custom Data Retention | Enterprise | ✓ | ✓ | Enterprise |
| No AI Training on Data | ✓ | ✓ | ✓ | Opt-out |
| Private Storage | Enterprise | ✓ | Limited | Enterprise |
Data Handling Best Practices
LLM Training Data Protection
The primary concern for enterprise organizations is ensuring meeting data isn't used to train AI models. Look for vendors with explicit policies that guarantee:
- • 0-day retention policies for AI training
- • Third-party AI vendors (OpenAI, Anthropic) also maintain no-training policies
- • Clear data processing agreements specifying data usage
- • Opt-out mechanisms for any data sharing
Meeting Recording Controls
Enterprise organizations should implement granular controls over what gets recorded:
- • Visible recording indicators for all participants
- • Pause/resume recording during sensitive discussions
- • Post-meeting redaction of confidential content
- • Department exclusion rules (legal, HR, executive)
- • Automatic consent collection and documentation
Access Permission Automation
Implement automated permission systems to prevent unauthorized access:
- • Role-based access tied to organizational hierarchy
- • Automatic deprovisioning when employees leave
- • Time-limited access for external participants
- • Approval workflows for sensitive meeting access
- • Regular access reviews and certification
Implementation Best Practices
Assess & Plan
Evaluate compliance requirements, assess current tools, and create implementation roadmap
Pilot & Validate
Deploy with small team (10-20 users), validate security controls, gather feedback
Scale & Monitor
Enterprise rollout with continuous monitoring, training, and quarterly security reviews
Key Implementation Steps:
- • Involve IT Security, Legal, Compliance, and HR stakeholders from the start
- • Document all security requirements before vendor selection
- • Negotiate Business Associate Agreements and Data Processing Agreements
- • Configure SSO, MFA, and RBAC before user onboarding
- • Establish incident response procedures and escalation paths
- • Plan mandatory security training for all users
- • Set up audit logging and regular compliance reporting
Common Security Risks to Address
Shadow IT Adoption
83% of organizations report employees installing AI tools faster than security teams can track. Mitigate by:
- • Providing approved enterprise alternatives
- • Implementing network monitoring for AI tools
- • Creating clear AI usage policies
Data Leakage Risks
Sensitive business data can be leaked through AI processing. Protect against this by:
- • Verifying no-training data policies
- • Implementing data classification systems
- • Using private storage options
Inadequate Vendor Oversight
Third-party AI vendors may have different security standards. Address by:
- • Reviewing sub-processor agreements
- • Verifying third-party certifications
- • Conducting regular vendor assessments
Insufficient Access Controls
Overly broad access to meeting recordings creates compliance risks. Resolve by:
- • Implementing least-privilege access
- • Automating access deprovisioning
- • Conducting quarterly access reviews
2025 Enterprise AI Security Trends
Key Statistics
- AI Spending: $644 billion forecasted for 2025
- Regulatory Concerns: Increased from 42% to 55% in one year
- Compliance Timeline: 3-11 months depending on framework
- SOC2 Adoption: Becoming baseline requirement for enterprise deals
Emerging Best Practices
- • Multi-framework compliance (SOC2 + GDPR + HIPAA)
- • AI-powered compliance monitoring tools
- • Zero-trust security architectures
- • Privacy-by-design in AI systems
- • Continuous compliance instead of point-in-time audits
