Check the system before work starts
Validate workload and platform integrity with hardware-backed trust signals before sensitive execution starts.
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Security checks for AI, devices, and sensitive data
Secure sensitive workloads in untrusted environments.
TeyzSec verifies devices and infrastructure before sensitive work runs, then keeps checking trust during execution so data stays inside approved environments — sovereign, defence and regulated.
Off
Primary focus
Protect data (AI) while in use
Supporting capability
Hardware-backed device and infrastructure checks
Selective capability
FHE for work that can accept extra processing time
Why this matters
Moving AI and regulated data into cloud, edge, or partner systems creates a second question not just who may sign in but: can the system itself still be safe and trusted? TeyzSec checks the system before sensitive work starts and continues checking while it runs. This matters most where the work cannot move: defence and government programmes, critical infrastructure, and regulated data that has to stay under national jurisdiction.
Primary product
InfraGuard
Continuous infrastructure trust for Kubernetes, Docker, and bare metal.
Verify servers before sensitive work runs, detect unexpected changes, trigger recovery workflows, and give customers signed proof tied to their workloads. This helps operators share machines across customers while keeping each customer's trust policy and evidence separate.
Drift detection in action
TPM/IMA-backed node trust
Continuous drift detection
Signed workload evidence
Higher rack utilization through verified multi-tenancy
Built for sovereign and defence-adjacent hosting
Production-proven solutions
Explore approaches used for 5G networks, medical research, and enterprise environments, with policies shaped for each setting.
How the platform protects sensitive work
How the platform protects sensitive work
Privacy-enhancing security FAQ
Plain answers about how TeyzSec checks systems and limits data exposure.
How can TeyzSec protect data while AI is using it?
Encryption commonly protects stored data and data being sent. Confidential computing also reduces exposure while approved systems process prompts, model inputs, and business data. It does not make every surrounding system automatically trustworthy, so the execution environment still needs to be checked and governed.
How does TeyzSec check whether a system can be trusted?
Attestation is a check that uses evidence from a device's hardware to show whether the device or software environment matches an approved state. TeyzSec checks that evidence before protected work begins and can deny work to systems that do not pass.
What happens if a trusted system changes while work is running?
TeyzSec keeps checking after startup. If the system no longer matches the approved state, configured policy can let it continue, isolate it, or start a controlled recovery. The response depends on the policy your team has set.
Can organizations train one model without pooling their raw data?
Federated Learning lets each organization train with data kept in its own environment. They share model updates rather than the underlying records. This reduces raw-data movement, but the updates and participating systems still require appropriate privacy and security controls.
Can TeyzSec work with data without first decrypting it?
For selected calculations, Fully Homomorphic Encryption (FHE) allows data to remain encrypted while it is processed. It adds substantial computing overhead, so it is best for highly sensitive analysis that does not need an immediate response.
Can TeyzSec check Android devices before allowing sensitive access?
Yes. TeyzSec checks hardware-backed evidence from supported Android devices on the server, then returns a trust decision that an application can use before allowing a sensitive workflow.
Protect the sensitive work your organization depends on.
Talk with us about where your sensitive data is processed and how system checks, runtime monitoring, or privacy technology could reduce exposure.