Enterprise Security for AI Deployments

Security is the non-negotiable foundation of any enterprise AI deployment. Organizations entrust AI characters with sensitive customer data, proprietary business information, and critical processes. This trust demands a comprehensive security approach that addresses data protection, access control, compliance, and ongoing monitoring.

The Enterprise Security Landscape

Enterprise AI deployments face unique security challenges. Unlike traditional software, AI systems can generate outputs that weren't explicitly programmed, potentially exposing sensitive information or behaving in unexpected ways. A robust security framework must address both conventional cybersecurity concerns and AI-specific risks.

Data Protection

Data Classification

Before deploying AI characters, classify the data they'll access:

**Public**: Information freely available to anyone

**Internal**: Non-sensitive business information

**Confidential**: Sensitive business data requiring protection

**Restricted**: Highly sensitive data with strict access controls

AI characters should be configured with appropriate access levels based on their function. A customer-facing support character shouldn't have access to internal financial data, even if it exists in connected systems.

Encryption Standards

Implement encryption at every layer:

**Data at Rest**: All stored conversation logs, character configurations, and training data should be encrypted using AES-256 or equivalent. At Wisent Platform, we encrypt all customer data with customer-managed keys, giving you complete control.

**Data in Transit**: All communications use TLS 1.3 minimum. This includes API calls, webhook deliveries, and inter-service communications within our infrastructure.

**Data in Use**: Sensitive data processed during inference should be protected using secure enclaves where available. This prevents even infrastructure administrators from accessing raw customer data.

Data Residency

Many enterprises face data residency requirements. Customer data from the EU must stay in the EU. Healthcare data might need to remain within specific jurisdictions.

Our platform supports region-specific deployments, ensuring that data never leaves designated geographic boundaries. This includes conversation logs, character training data, and even inference processing.

Access Control

Identity and Access Management

Integrate AI character administration with your existing identity provider. We support:

SAML 2.0 for enterprise SSO

OIDC for modern authentication flows

SCIM for automated user provisioning

This ensures that AI character access follows your existing governance policies and user lifecycle management.

Role-Based Access Control

Define granular roles for AI character management:

**Viewer**: Can see character performance metrics

**Operator**: Can modify operational parameters (response limits, escalation thresholds)

**Editor**: Can modify character personality and behavior

**Administrator**: Full access including deletion and security settings

The principle of least privilege should guide role assignments. Most users need only Viewer or Operator access.

API Security

For programmatic access, implement:

API keys with automatic rotation

OAuth 2.0 for user-context operations

IP allowlisting for sensitive operations

Rate limiting to prevent abuse

All API access should be logged and auditable.

Compliance Frameworks

SOC 2 Type II

Our platform maintains SOC 2 Type II certification, demonstrating ongoing compliance with trust service criteria:

Security: Systems are protected against unauthorized access

Availability: Systems are available for operation as committed

Processing Integrity: System processing is complete and accurate

Confidentiality: Information designated as confidential is protected

Privacy: Personal information is collected and used appropriately

GDPR

For organizations operating in or serving the EU, AI deployments must comply with GDPR:

**Right to Access**: Users can request all data the AI has about them

**Right to Deletion**: Users can request data deletion

**Data Minimization**: Collect only necessary data

**Purpose Limitation**: Use data only for stated purposes

Our platform includes built-in tools for handling data subject requests and maintaining processing records.

HIPAA

Healthcare organizations need HIPAA-compliant AI deployments. This requires:

Business Associate Agreements (BAAs)

Access controls and audit logging

Encryption of protected health information

Breach notification procedures

We offer HIPAA-compliant deployment options with appropriate technical and administrative safeguards.

AI-Specific Security

Prompt Injection Prevention

Malicious users may attempt to manipulate AI characters through carefully crafted inputs. Our defense-in-depth approach includes:

Input sanitization and validation

Behavioral guardrails that resist manipulation

Representation engineering that makes character behavior more robust than prompt-based approaches

Anomaly detection that flags unusual interaction patterns

Output Filtering

AI characters might inadvertently generate inappropriate or sensitive content. Implement:

Content filters for harmful or inappropriate outputs

PII detection to prevent accidental data exposure

Brand compliance checks for customer-facing characters

Confidence thresholds that trigger human review

Model Security

The AI models themselves require protection:

Character configurations contain valuable intellectual property

Model weights and control vectors should be encrypted

Access to model infrastructure should be strictly controlled

Regular security assessments should include AI-specific threat modeling

Monitoring and Incident Response

Continuous Monitoring

Implement real-time monitoring for:

Unusual access patterns

Spike in error rates

Unexpected character behavior

Performance degradation

Integrate AI monitoring with your existing security operations center (SOC) for unified incident management.

Incident Response

Develop AI-specific incident response procedures:

**Detection**: Automated alerts or user reports identify potential issues

**Containment**: Ability to instantly disable specific characters or features

**Investigation**: Comprehensive logs enable root cause analysis

**Remediation**: Clear procedures for addressing different incident types

**Recovery**: Tested procedures for restoring normal operation

**Lessons Learned**: Post-incident reviews improve future response

Audit Logging

Maintain comprehensive audit logs:

All character configuration changes

All administrative access

All API calls with request/response metadata

All conversation summaries (respecting privacy requirements)

Logs should be tamper-evident and retained according to compliance requirements.

Security Best Practices

Regular Assessments

Conduct regular security assessments including:

Quarterly penetration testing

Annual third-party audits

Continuous vulnerability scanning

AI-specific red team exercises

Vendor Management

If using third-party AI components, evaluate vendor security:

Review their security certifications

Understand their data handling practices

Ensure contractual security commitments

Monitor vendor security disclosures

Employee Training

Security is a people problem. Train employees on:

Recognizing AI-related security risks

Proper handling of AI-related incidents

Security implications of character modifications

Social engineering attacks targeting AI systems

Conclusion

Enterprise AI security requires a comprehensive approach that addresses traditional cybersecurity concerns plus AI-specific risks. By implementing robust data protection, access controls, compliance frameworks, and monitoring, organizations can deploy AI characters with confidence.

At Wisent Platform, security isn't an afterthought. It's built into every layer of our architecture. Contact our security team to discuss how we can help secure your AI deployment.