Confidential AI Data Pipeline Architecture

Achieve compliance with data-in-use mandates (GDPR, HIPAA, EU AI Act) without sacrificing development speed. Our certified TEE integration for AI workloads enables deployment of sensitive AI applications in weeks, not months, by providing a pre-validated security architecture.

Safeguard multi-million dollar investments in proprietary algorithms and training data. By executing AI inference and fine-tuning within encrypted enclaves, model weights and sensitive datasets are cryptographically isolated from the host OS, cloud admins, and other tenants, mitigating insider threat and IP theft. Learn more about our approach to encrypted AI model deployment and management.

Unlock new revenue streams and insights through secure multi-party computation. Our confidential AI pipeline architecture allows partners—such as hospitals for clinical trials or banks for fraud detection—to jointly train models on combined datasets without ever exposing raw, sensitive data to each other.

Minimize exposure to catastrophic data breaches and regulatory fines. A verifiable confidential computing posture, with remote attestation, provides demonstrable evidence of security controls for auditors and insurers, potentially lowering cyber insurance premiums and strengthening stakeholder trust.

Build infrastructure that adapts to evolving global data sovereignty laws. Our designs for confidential AI in hybrid cloud architectures ensure sensitive processing can be dynamically routed to geopatriated TEEs, whether on-premise or in a compliant cloud region, preventing costly re-architecture later.

Deliver secure AI without compromising on latency or throughput. We specialize in hardware-secured AI for financial trading and other performance-critical applications, leveraging direct integration with TEE-capable CPUs and accelerators to maintain sub-millisecond inference speeds under full encryption.

Secure processing of PHI and genomic data for clinical decision support and drug discovery within Intel SGX/AMD SEV enclaves, enabling HIPAA-compliant AI without data centralization.

Execution of proprietary trading algorithms, fraud detection models, and sensitive risk analytics in attested AWS Nitro Enclaves, protecting IP and PII from cloud provider and insider threats.

Deployment of air-gapped, hardware-rooted AI for geospatial intelligence and secure communications, ensuring model integrity and preventing data exfiltration on potentially compromised infrastructure.

Confidential analysis of privileged legal documents and contract data within TEEs to automate discovery and compliance checking, ensuring attorney-client privilege is technically enforced.

Hardware-secured facial recognition and fingerprint matching where biometric templates and live data are processed entirely in encrypted memory, preventing replay attacks and template theft.

Secure multi-party computation for joint AI training across jurisdictions (e.g., multi-hospital trials), enabling insights from combined datasets without moving or exposing raw sensitive data.