Use case VectaX AgentIQ

Stop your model from being cloned out the back door

Distillation defence built into the encryption layer. Query patterns that exfiltrate the model fail before they get a useful gradient.

Computes on data it can never see

Enterprise SaaSFinancial servicesHead of AIEngineering leadInference providersSaaS embedding AI

The problem

Distillation attacks turn your API into someone else's competing model in weeks.

A few weeks of distillation queries and your hard-won model is now powering a competitor's API.

Mirror restores Encryption · FHE · computes on data it can never see

How it works

01

Watch

AgentIQ profiles query patterns for the signatures of extraction and distillation.
02

Seal

VectaX keeps the model's internals encrypted so probing never yields a useful gradient.
03

Cut off

Exfiltration patterns fail before they reconstruct anything worth stealing.

Knowledge bases, vector stores, conversation history, agent memory. Every piece of context an AI reaches for is plaintext the moment it's loaded.

Domain models need real customer data to be useful. Training in plaintext means you hold what you swore you wouldn't.

Defence, government, and regulated workloads can't legally move data outside their boundary. So they're locked out of AI entirely.

Get started

FHE-native inference. Runtime agent guardrails. Continuous red teaming. One platform. Book a working session with the team.