Secure voice AI built for enterprise conversations
Convrz AI is designed to help organizations deploy intelligent voice agents while protecting the sensitive data that moves through every conversation.
Voice AI is not just another chatbot. It handles live audio, transcripts, caller metadata, business context, customer records, and workflow actions. That means security cannot be treated as an afterthought. At Convrz AI, data protection is built into the way our platform captures, processes, stores, transmits, and governs conversational data.
Our security approach is based on industry best practices for encryption, access control, data minimization, operational monitoring, secure integrations, and responsible AI governance.
Our security philosophy
Convrz AI is built around a simple principle:
Your conversations belong to you.
We design our platform to protect customer data across the full voice AI lifecycle, from the moment a call is received to the moment data is processed, stored, routed, retained, or deleted.
Our security model focuses on:
Protecting voice recordings, transcripts, and caller information
Restricting access to authorized users only
Encrypting data in transit and at rest
Minimizing unnecessary data retention
Maintaining clear auditability across platform activity
Supporting secure integration with customer systems
Applying governance controls to AI behavior and data handling
Because apparently letting an AI voice agent roam free through customer data like a raccoon in a server room is considered “innovation” by some people. Not here.
Data we protect
Convrz AI may process different categories of data depending on the customer deployment, configuration, and integrations enabled.
This may include:
Voice call audio
Real-time transcriptions
Call summaries
Caller phone numbers and metadata
Customer-provided business rules
Appointment, support, or service request details
Integration data exchanged with customer systems
AI agent configuration and prompts
Conversation analytics and quality signals
Escalation and handoff records
For healthcare, financial services, insurance, or other regulated use cases, additional safeguards can be applied based on contractual, operational, and compliance requirements.
Encryption in transit
Convrz AI protects data as it moves between systems using secure transmission methods aligned with modern industry practices.
This includes encrypted connections between:
Caller channels and voice infrastructure
Convrz AI services and orchestration layers
Speech-to-text and text-to-speech services
Customer applications and APIs
Admin dashboards and authenticated user sessions
Integrated systems such as CRMs, scheduling systems, helpdesks, or EMRs
Where supported by the deployment architecture, Convrz AI uses TLS-based secure transmission to reduce the risk of interception, tampering, or unauthorized exposure while data is in motion.
Encryption at rest
Sensitive data stored by Convrz AI is protected using encryption at rest where applicable.
This may include:
Stored call recordings
Conversation transcripts
Call summaries
Configuration data
Customer-specific knowledge and business rules
Analytics data
Operational logs containing limited metadata
Encryption at rest helps protect stored information if infrastructure, storage systems, or backups are accessed without authorization.
Customer data isolation
Convrz AI is designed for multi-tenant environments where data separation is critical.
Our architecture supports logical isolation between customer environments to help ensure that each organization’s data, configurations, workflows, and AI agents remain separated from other customers.
This includes controls for:
Tenant-specific access
Customer-specific agent configuration
Separated business logic and workflows
Restricted administrative permissions
Environment-based segmentation
Controlled access to production data
For enterprise deployments, Convrz AI can support dedicated environments or additional isolation patterns based on customer requirements.
Access control
Convrz AI follows the principle of least privilege, meaning users and internal systems should only have access to the data and capabilities needed to perform their role.
Access control capabilities may include:
Role-based access control
Admin-managed user permissions
Google SSO or enterprise identity integration
Restricted platform access by approved users
Strong authentication requirements
Environment-level access separation
Administrative approval for sensitive access
Periodic access review processes
This helps ensure that customer data is not exposed broadly across users, teams, or vendors.
Authentication and SSO
Convrz AI supports secure authentication patterns for platform access.
For enterprise customers, this may include:
Google Sign-In
Single sign-on support
Admin-approved user access
Domain-level access policies
Multi-tenant user management
Restricted administrative controls
Only authorized users should be able to access the Convrz AI platform, configure agents, view conversations, manage integrations, or access reporting.
Audit logs and monitoring
Security is not only about blocking access. It is also about knowing what happened, when it happened, and who performed the action.
Convrz AI supports auditability across key platform events, including:
User login activity
Agent configuration changes
Integration activity
Access to sensitive conversation data
Administrative updates
Workflow execution events
System-level operational events
Monitoring and logging help support incident detection, operational troubleshooting, compliance review, and customer accountability.
Data retention and deletion
Convrz AI supports data retention practices that can be configured based on customer requirements.
Depending on the deployment, customers may define retention rules for:
Call recordings
Transcripts
Conversation summaries
Analytics data
Metadata
Logs
Integration payloads
Convrz AI can support data deletion workflows based on contractual obligations, customer policy, regulatory requirements, or operational needs.
Our recommended approach is to retain only what is needed for business, compliance, quality assurance, and support purposes. Anything else is just digital hoarding with a fancier name.
AI model and training data policy
Customer conversation data should be handled with clear boundaries.
Convrz AI does not use customer production data to train shared public models unless explicitly authorized by the customer in writing.
Customer-specific data may be used to configure, tune, evaluate, or improve that customer’s own AI agents only when permitted by contract and deployment scope.
This helps protect sensitive business data, caller information, and proprietary customer workflows from unintended reuse.
Voice AI governance
Security in voice AI is not limited to encryption. The AI agent’s behavior also needs governance.
Convrz AI applies guardrails to control what voice agents can say, do, access, and escalate.
Governance capabilities may include:
Approved answer boundaries
Customer-specific business rules
Escalation logic
Restricted topics
Compliance disclaimers
Safe fallback responses
Human handoff rules
Call recording disclosures
Policy-based workflow execution
This is especially important in industries such as healthcare, financial services, insurance, travel, telecom, and government services, where one confident wrong answer can become a full corporate migraine.
Secure integrations
Convrz AI can integrate with customer systems to perform actions such as scheduling, ticket creation, insurance verification, account lookup, SMS follow-up, CRM updates, and workflow routing.
Security controls for integrations may include:
API authentication
Encrypted API communication
Scoped access tokens
Environment-specific credentials
Credential rotation
Limited data exchange
Logging of integration events
Customer-approved integration workflows
We design integrations so the AI agent receives only the information needed to complete the task, not the entire corporate nervous system.
Healthcare and regulated deployments
For healthcare use cases, Convrz AI can support HIPAA-aligned safeguards depending on deployment scope, customer requirements, and contractual terms.
Healthcare-focused deployments may include:
Administrative safeguards
Technical safeguards
Access control
Audit controls
Transmission security
Encryption controls
Role-based permissions
BAA support where applicable
Workflow governance for patient-facing interactions
The HIPAA Security Rule requires covered entities and business associates to use administrative, physical, and technical safeguards to protect electronic protected health information, so healthcare voice AI deployments need more than “the demo sounded good.”
Compliance alignment
Convrz AI’s security program is designed to align with widely recognized security and privacy frameworks, including:
NIST Cybersecurity Framework
SOC 2 Trust Services Criteria
HIPAA Security Rule for applicable healthcare deployments
Cloud security best practices
Least-privilege access principles
Secure software development practices
Data minimization and retention controls
NIST SP 800-53 provides a catalog of security and privacy controls for organizations and systems, while SOC 2 evaluates controls related to security, availability, processing integrity, confidentiality, and privacy.
Vendor and subprocessor security
Voice AI platforms often rely on specialized infrastructure and service providers, such as telephony, speech recognition, text-to-speech, cloud hosting, observability, messaging, and workflow automation services.
Convrz AI evaluates vendors based on their role in the data flow, security posture, contractual protections, and operational relevance.
Where applicable, Convrz AI can provide information about subprocessors involved in a customer deployment.
Privacy by design
Convrz AI applies privacy-minded design principles across the platform.
This includes:
Collecting only the data required for the use case
Avoiding unnecessary exposure of sensitive information
Limiting access to authorized users
Supporting customer-defined retention rules
Reducing sensitive data in logs where possible
Designing AI workflows around approved business purposes
Supporting secure escalation to human teams
The goal is simple: make the AI useful without turning every phone call into a data landfill.
Enterprise security review
Convrz AI supports security and technical due diligence for enterprise customers.
Upon request and where appropriate, we can provide:
Security architecture overview
Data flow diagrams
Integration security review
Encryption and access control overview
Vendor and subprocessor details
Deployment-specific risk review
Healthcare safeguard review
Commercial and technical security documentation under NDA
Security FAQ
Does Convrz AI encrypt voice AI data?
Yes. Convrz AI is designed to protect data in transit and at rest using encryption practices aligned with modern cloud and enterprise security standards.
Does Convrz AI use customer data to train public models?
No. Customer production data is not used to train shared public models unless explicitly authorized in writing.
Can customers control retention periods?
Yes. Retention policies can be configured based on customer requirements, deployment scope, and contractual obligations.
Does Convrz AI support HIPAA-aligned deployments?
Yes. For healthcare use cases, Convrz AI can support HIPAA-aligned safeguards and BAA-backed deployment models where required.
Can Convrz AI integrate securely with our systems?
Yes. Convrz AI supports secure integrations through authenticated APIs, scoped access, encrypted communication, and customer-approved workflows.
Does Convrz AI support SSO?
Yes. Convrz AI can support enterprise authentication patterns such as Google Sign-In and SSO-based access control.
Can customers request security documentation?
Yes. Enterprise customers can request security documentation, architecture reviews, data flow diagrams, and vendor details as part of due diligence.