How the trust layer is built.
The architecture under Mirror Security. Encrypted compute, cryptographic identity, runtime policy, and continuous adversarial validation. Designed for large, regulated, agentic environments.
The platform at a glance
Inputs flow in. Encrypted decisions flow out.
Every input (prompts, RAG embeddings, agent actions, model calls) passes through three coordinated pillars before reaching production.
How it works
A coordinated stack that secures every call.
Encrypted compute, cryptographic identity, runtime policy, and continuous adversarial testing. Each layer enforces something different. Together they cover the full AI attack surface.
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Encrypt at the source
VectaX wraps inputs, prompts, and vectors in FHE before they leave the client. Nothing decrypts on its way through your stack.
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Compute on ciphertext
Inference and vector search run on encrypted data. The model produces an encrypted response. Plaintext never lands in RAM.
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Gate every agent action
AgentIQ is the control plane: every agent carries a signed identity and capability scope, every tool call is gated by runtime policy, every decision leaves a plain-English receipt. Nothing acts without authorization.
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Pressure-test continuously
DiscoveR runs 1,050+ attack templates across 60+ attack types. Find the failure before an attacker does.
Architecture
Built for production AI at scale.
A coordinated system of encrypted compute, cryptographic identity, policy enforcement, and continuous red teaming. Designed for large, regulated, agentic environments.
See it in action
The architecture, on your stack.
A working session with the team: walk through the layers against your AI workload, your regulator's requirements, and your deployment constraints.