Conversational AI agents are quickly becoming the interface between businesses and their customers. They answer support requests, process payments, schedule appointments, perform identity verification, assist clinicians, and automate internal operations. Unlike traditional application logs, **AI observability captures the entire context of an interaction: voice recordings, transcripts, tool calls, prompts, model responses, evaluation traces, and business metadata**. These traces often contain the most sensitive information an organization handles. As an observability and testing platform for conversational AI, Cekura sits in the middle of this data flow. That responsibility fundamentally shapes how we design our infrastructure. Security cannot be a feature layered on top of an AI platform. It has to be an architectural principle that influences every decision - from how data is stored and accessed to how it is retained and ultimately deleted. ## Security by Design Security is strongest when every component assumes the one before it can fail. Instead of relying on a single security boundary, the platform follows a defense-in-depth approach where independent layers work together to protect customer data. **Encryption is the baseline, not the security strategy.** Our platform applies security controls across every major layer of the stack: - **Network:** Strict TLS enforcement for all communication. - **Storage:** Industry-standard encryption for databases, caches, and object storage. - **Application:** Field-level encryption for highly sensitive assets such as provider API keys and webhook secrets. - **Identity:** Strong authentication and scoped access controls that ensure every request is verified before access is granted. Rather than trusting a single security mechanism, **every layer is designed to limit the impact of a failure in another** - providing multiple independent safeguards for the conversations, traces, and secrets entrusted to Cekura. ![Defense-in-depth security layers for voice AI observability](/blogs/images/securing-conversational-ai-observability/defense-in-depth.png) ## Identity, Access, and Tenant Isolation In a multi-tenant platform, the strongest security boundary is the boundary between organizations. Every request to Cekura must prove two things: **who it is** and **what organization it belongs to**. Access controls are enforced throughout the platform to ensure conversations, transcripts, evaluations, and API resources remain isolated to their respective tenants. For organizations with strict compliance requirements, cryptographically signed memberships provide tamper-evident access boundaries that are tightly coupled to organizational context. The same philosophy extends to authentication and machine access: - **Enterprise authentication:** Multi-factor authentication (MFA) and native support for enterprise Single Sign-On (SSO). - **Scoped API credentials:** Keys are cryptographically hashed at rest, restricted to specific projects, displayed only once during creation, and designed for seamless rotation. - **Customer-controlled access:** Platform engineers and support staff do not have privileged "superuser" access to customer conversations or transcripts. Any support access must be explicitly authorized and remains fully auditable. Identity isn't treated as a login feature - it's a core security primitive that defines every interaction with the platform. ## Privacy by Default: PHI Redaction AI observability is only valuable if it can be used without creating unnecessary privacy risk. Whether you're building healthcare assistants, financial systems, or customer support agents, teams need full visibility into AI behavior without exposing sensitive user data. > **The safest sensitive data is the data you never retain.** The platform supports end-to-end redaction of sensitive information, ensuring that personally identifiable and regulated data can be removed before it even leaves their infrastructure in the first place. This flexibility allows organizations to define where privacy enforcement happens based on their regulatory and operational requirements, while still enabling full observability of conversational AI systems. ## Your Data, Your Lifecycle Security is not just about preventing unauthorized access. It is also about giving organizations complete control over the lifecycle of their data. - **Retention control:** Call recordings, transcripts, logs, and evaluation traces can be automatically archived or permanently deleted based on compliance requirements. - **Auditability:** Every action performed within the platform - whether by a user or an API integration - is captured and can be retrieved in comprehensive audit logs that record the actor, action, source, and organizational scope. - **Data ownership and export:** Customers retain full ownership of their data. All conversational artifacts and analytics can be exported programmatically at any time for internal analysis. - **Deletion control:** When data needs to be removed, it is removed. Cekura supports deletion-on-demand workflows that enable organizations to meet internal governance requirements and regulatory obligations. ## Data Sovereignty and VPC Deployments Enterprises increasingly require strict guarantees about where their data is stored and processed. The platform supports regional data residency across the United States, Europe, India, and other supported regions, ensuring that **all databases, storage systems, caches, and processing infrastructure remain confined within a selected geography.** For organizations with stricter requirements, the platform can also be deployed as a **Bring Your Own Cloud (BYOC)** configuration that runs entirely within the customer's own cloud environment. In this model: - **Full environment control:** Organizations retain complete control over their infrastructure boundaries while operating Cekura entirely within their own cloud environment. - **Managed operations:** First-class support for provisioning, upgrades, and ongoing maintenance is built into the platform, enabling teams to adopt a BYOC setup without adding operational overhead. - **Secure integrations:** BYOC deployments support customer-managed credentials, including external LLM providers and API keys, allowing full integration with existing AI and security stacks while maintaining control over sensitive dependencies. ## Trust Through Verification: SOC 2, HIPAA, and GDPR

Enterprise trust cannot rely on promises alone. It must be independently validated. Cekura maintains industry-standard security and compliance programs and is **SOC 2 Type II certified, HIPAA compliant, and GDPR certified**. All external partners involved in delivering the platform - including telephony providers and LLM vendors - are **governed through appropriate Business Associate Agreements (BAAs)** ensuring that security and privacy obligations extend across the entire supply chain. We also maintain a clear commitment: **customer data is never used to train foundation AI models.** All conversational data, prompts, transcripts, and evaluation traces remain the property of the customer and are protected by contractual safeguards. Beyond compliance, the platform undergoes continuous independent penetration testing and ongoing security assessments to proactively identify and address vulnerabilities. ### What Compliance Reviewers Typically Ask For Different frameworks expect different artifacts. Cekura maintains the evidence chain across all three: | Framework | Evidence buyers and auditors typically request | |---|---| | SOC 2 Type II | Continuous monitoring logs, access logs, control attestations | | HIPAA | BAA on file, encryption proofs, breach response runbook, access audit trail | | GDPR | Data inventory, subprocessor list, deletion proofs, consent records | ## Frequently Asked Questions **How does PHI redaction work in voice AI?** PHI redaction scrubs personally identifiable healthcare information at the transcript layer and within audio recordings before storage. It applies to ASR output, audio recordings, tool call payloads, and observability logs. Effective redaction operates pre-persistence so sensitive data is removed end-to-end across primary stores, backups, and search indexes. **Can a voice AI platform be HIPAA compliant?** A voice AI platform can be HIPAA compliant if it provides BAAs covering its subprocessors, PHI redaction at all storage layers, tenant isolation, encryption at rest and in transit, and audit-ready access logs. Cekura is HIPAA compliant and maintains BAAs with subprocessors that touch PHI. **What audit evidence do compliance reviewers expect for voice AI?** SOC 2 reviewers expect continuous monitoring and access logs. HIPAA reviewers expect signed BAAs, encryption proofs, breach runbooks, and access audit trails. GDPR reviewers expect data inventories, deletion proofs, consent records, and subprocessor lists. **How is data residency handled in multi-region AI observability?** Regional data residency pins all databases, storage, caches, and processing infrastructure within a selected geography. Cross-region replication does not occur unless explicitly configured. Cekura supports residency across the United States, Europe, and India. **What is BYOC for AI observability, and when does it make sense?** Bring Your Own Cloud (BYOC) is a deployment model where the AI observability platform runs entirely within the customer's own cloud account. It makes sense for organizations that need strict guarantees that conversational data never leaves their cloud environment - typically in regulated industries or for customers with specific sovereignty requirements. ## Ready to Secure Your AI Operations? Building confidence in your conversational AI starts with robust, secure observability. [Book a demo](https://www.cekura.ai/expert) with our team to discuss your security requirements, or [start your free trial](https://dashboard.cekura.ai/sign-up) to explore the Cekura platform today.

Posts tagged with "Hipaa"

Securing Conversational AI Observability at Cekura