Attestation
Hardware-rooted cryptographic evidence that a device, workload, or runtime is in an approved state before it can process protected data.
How TeyzSec applies attestation in productionLoading TeyzSec
Securing your experience...
Securing your experience...
TeyzSec combines hardware-rooted attestation, continuous runtime verification, policy-based enforcement, federated learning, and selective fully homomorphic encryption — so sensitive processing runs only on approved infrastructure.
Primary focus
Confidential computing for AI workloads
Supporting capability
Hardware-backed device trust and attestation
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.
Battle-tested in 5G networks, medical research, and enterprise environments — each packaged with industry-specific policy profiles.
Device and infrastructure integrity verification across six verticals — enterprise, gaming, banking, healthcare, BYOD, and field devices — plus mobile device trust for Android.
Collaborative ML across institutions while raw data stays local — exchange model updates, not datasets.
Explore federated learning SolutionComputation on encrypted data, without decryption.
Explore SolutionPrivacy solutions tailored to your needs.
Explore View all privacy-enhancing security solutions and use casesProduct
TeyzSec Mobile Trust validates hardware-backed attestation server-side and returns an enforceable trust decision before sensitive mobile access.
See Mobile TrustProduct
InfraGuard proves workloads ran on TPM-attested, policy-compliant Kubernetes, Docker, and bare-metal nodes — with signed evidence reports and drift alerts.
See InfraGuardCapability
For delay-tolerant, high-sensitivity analytics, TeyzSec applies Fully Homomorphic Encryption so batch computation runs without exposing raw data.
Explore FHEValidate 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.
Concise terminology for technical buyers and security architecture teams evaluating deployment options.
Hardware-rooted cryptographic evidence that a device, workload, or runtime is in an approved state before it can process protected data.
How TeyzSec applies attestation in productionA collaborative ML approach where participants train a shared model while raw datasets remain local, exchanging model updates rather than source data.
Explore federated learning architecturesCryptographic processing that enables computation directly on encrypted data, so sensitive inputs stay encrypted throughout outsourced or shared analytics.
Review enterprise FHE use casesA class of engineering techniques — attestation, federated learning, and encryption-centric controls — that reduce exposure of sensitive data while preserving utility.
See custom PET implementation patternsDesigned 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.
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
Common questions about our confidential computing and privacy-enhancing solutions.
Book a technical briefing to see how TeyzSec can secure AI and sensitive processing in your cloud, edge, and partner environments.