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Securing your experience...
Securing your experience...
TeyzSec combines hardware-rooted trust, continuous runtime verification, policy-based enforcement, and selective privacy-preserving analytics to ensure sensitive processing runs only on approved infrastructure.
Primary Focus
Confidential computing for AI workloads
Supporting Capability
Working Android device trust verification
Selective Capability
FHE for latency-insensitive analytics
As enterprises move models, prompts, embeddings, and regulated data into cloud, edge, and partner environments, the risk is not only who can access a system, but whether the system is trustworthy while computation is happening. TeyzSec closes that gap by verifying integrity before execution and enforcing trust continuously at runtime.
Validate workload and platform integrity with hardware-backed trust signals before sensitive execution starts.
Verify trust during execution, detect drift or tampering, and keep high-value workloads inside approved conditions.
Isolate policy-violating workloads and trigger controlled recovery to clean instances when trust posture changes.
Use FHE for delay-tolerant, high-sensitivity analytics when data exposure risk is unacceptable.
TeyzSec includes a working Android attestation capability where a trusted server validates hardware-backed attestation evidence and returns an enforceable trust decision. This supports sensitive workflows such as approvals, records access, privileged operations, and regulated mobile transactions.
For delay-tolerant, high-sensitivity analytics, TeyzSec can apply Fully Homomorphic Encryption so batch-oriented computation can run without exposing raw data. Real-time systems continue to use the confidential-computing trust path.
Designed for Kubernetes clusters, edge deployments, and mixed trust environments.
Approach validated in a Kubernetes-based 5G core environment under real deployment conditions.
Protect model logic and sensitive inference data while enforcing runtime trust policies.
Collect hardware-backed trust evidence before critical workload execution.
Continuously verify integrity during live processing.
Allow, isolate, or recover workloads based on enforceable policy.
Secure AI inference for enterprise SaaS
Secure RAG and document intelligence
Third-party AI processing assurance
Fraud and risk scoring protection
Secure edge AI for industrial systems
Sovereign and public-sector AI workloads
Book a technical briefing to see how TeyzSec can secure AI and sensitive processing in your cloud, edge, and partner environments.