What is AI Security and Compliance?

Meet HIPAA, SOC 2, FedRAMP, and ITAR requirements with security built into every layer of your AI stack. Oaken AI provides ai security and compliance services for established businesses looking to implement AI that delivers measurable results.

Who needs ai security and compliance?

AI Security and Compliance is designed for established businesses — professional services firms, local businesses, agencies, and e-commerce companies — that want to save time and reduce manual work through AI automation. If your team spends hours on repetitive tasks each week, this service can help.

How long does ai security and compliance take to implement?

Oaken AI delivers working systems in as little as 7 days. We start with your highest-impact bottleneck and build a functional system before expanding to other areas. No multi-month assessments or slide decks — just results.

Do I need technical expertise for ai security and compliance?

No. Oaken AI handles the entire technical implementation. You do not need to hire an AI team, learn to code, or understand machine learning. We build systems your existing team can use and maintain.

AI Security & Compliance | HIPAA SOC 2 FedRAMP ITAR | Oaken AI

Compliance-First AI Architecture

Regulated industries cannot adopt AI by bolting security on afterdeployment. Compliance requirements must inform architecture decisions from the start: where data resides, who can access it, how long it is retained, and what audit evidence is generated. We design AIinfrastructure that satisfies your compliance framework from day one, so your security and legal teams approve the deployment rather than blocking it.

HIPAA Compliance

Protected health information processed by AI within your BAA-covered infrastructure. Encryption at rest and in transit, minimum necessary access, audit logging, and automatic PHI detection in prompts and responses.

SOC 2 Type II

Security, availability, and confidentiality trust service criteria mapped to AI infrastructure controls. Continuous monitoring, access reviews, change management, and incident response procedures documented and auditable.

FedRAMP Authorization

Federal cloud AI deployments meeting FedRAMP Moderate or High baselines. NIST 800-53 controls implemented across compute, network, identity, and data layers. Continuous monitoring with ConMon reporting.

ITAR Controls

Defense AI workloads restricted to U.S. persons with appropriate clearances. Physical and logical access controls, data handling procedures, and export control compliance for AI models processing controlled technical data.

Compliance Implementation Process

Assess

Map regulatory requirements to controls

Design

Architecture meeting control requirements

Implement

Deploy with security controls active

Audit

Generate evidence for compliance reviews

Assess

Map regulatory requirements to controls

Design

Architecture meeting control requirements

Implement

Deploy with security controls active

Audit

Generate evidence for compliance reviews

Security & Compliance Posture

Encryption Architecture

Data protection at every stage of the AI inference pipeline requires layered encryption that covers data in transit, at rest, and in use.

In-transit encryption. TLS 1.3 for all API communication. Mutual TLS (mTLS) for service-to-service communication within the inference pipeline. Certificate management through your PKI or cloud-managed certificate services (ACM, Azure Key Vault, GCP Certificate Manager).

At-rest encryption. AES-256 encryption for stored prompts, responses, model weights, and log files. Encryption keys managed in your HSM (CloudHSM, Azure Dedicated HSM) or cloud KMS with key rotation policies. Customer-managed keys ensure your organization controls decryption.

In-use protection. Confidential computing with AMD SEV-SNP or Intel TDX creates encrypted memory enclaves around the inference process. Eveninfrastructure administrators cannot access data during processing. Available on AWS (Nitro Enclaves), Azure (Confidential VMs), and GCP (Confidential Computing).

Authentication and Authorization

Every actor in the AI infrastructure, human users, service accounts, and automated processes, must be authenticated and authorized with the principle of least privilege.

Identity federation. Integration with your identity provider (Azure AD, Okta, Ping) via SAML 2.0 or OIDC. No local accounts on AI infrastructure. MFA enforcement for human access. Short-lived tokens for service accounts with automatic rotation.

Role-based access control. Separate roles for model consumers (inference only), model operators (deployment and configuration), and model administrators (full access including model updates and security policy changes). Mapped to your IdP groups for centralized management.

Audit trail. Every access event logged with identity, action, timestamp, and outcome. Immutable log storage with configurable retention periods. Integration with your SIEM for correlation with other security events.

Who This Is For

Security and compliance architecture is essential for any organization in a regulated industry deploying AI. If your AI adoption is blocked by security review, compliance concerns, or legal risk assessment, we design the infrastructure that gets those stakeholders to yes.

AI Security and Compliance