How the trust layeris 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 thatsecures 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.
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.
Compute on ciphertext
Inference and vector search run on encrypted data. The model produces an encrypted response. Plaintext never lands in RAM.
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.
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.