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← Use Cases · CONFIDENTIAL COMPUTING

Sovereign Confidential Computing

AllEyes ResilientGARANCE PKI
01 — Analysis

Problem

Confidential workloads (medical AI, finance, defense) require attestable and auditable Trusted Execution Environments (TEE). Existing solutions (Intel TDX, AMD SEV-SNP) rely on centralized attestation services often outside the EU, and inter-TEE key exchange still uses classical RSA/ECDH — incompatible with PQC migration.

CryptOps Solution

AllEyes Resilient runs a sovereign remote attestation platform with ML-DSA-87 and acts as a PQC KMS for the fleet's AMD SEV-SNP TEEs on EPYC hosts. The FPGA accelerates memory encryption operations and the GPU runs confidential inference on encrypted models.

Deployment architecture

02 — Performance

Key metrics

SEV-SNP
+ TDX compat.
TEE support
ML-DSA-87
native PQC
Attestation
AES-XTS
hardware
Memory encrypt
CCA
Confidential Computing
Compliance
03 — ROI

ROI analysis

Item Before With CryptOps Impact
External attestation service Outside EU (Intel/Azure) Local GARANCE PKI Sovereignty
TEE PQC migration Incompatible Native ML-DSA-87 Future-proof
Sensitive AI inference Non-confidential cloud Local TEE + GPU Secret preserved
04 — Compliance

Applicable regulation

CCA (Confidential Computing Architecture)
CCC consortium standard

Attestation and isolation framework for confidential workloads.

SecNumCloud v3.2
Tenant isolation

Attestable TEE acceptable for sovereign CSP qualification.

AI Act · sensitive models
Model protection

TEE inference for systemic-risk AI models (GPAI).

05 — Target clients

Target clients

Sovereign CSPs Sensitive AI enterprises (healthcare, defense) Confidential data analytics platforms Multi-party research consortia
06 — Business applications

Data processing on the same appliance

Beyond post-quantum encryption, every AllEyes Resilient appliance hosts your data-processing workloads on its FPGA, CPU and GPU resources — all isolated from the certified crypto core.

Next step

Secure your infrastructure today

Our team will guide you through the deployment tailored to your use case.