Use case Gateway VectaX

Pick the encryption posture per workload, not per gateway

Plain, end-to-end, FHE, and Local lanes configured route-by-route. Latency and exposure tuned to the workload.

Computes on data it can never see

Engineering leadHead of AIInference providersSaaS embedding AI

The problem

Some routes need raw speed. Others need FHE all the way through. You shouldn't have to pick one for the whole org.

Force one encryption posture on the whole org and you either throttle the fast paths or expose the sensitive ones.

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

How it works

01

Classify

Tag each route by sensitivity and latency budget. not the whole gateway at once.
02

Assign a lane

Pick Plain, end-to-end, FHE, or Local per route. VectaX and Gateway enforce the posture you chose.
03

Tune

Move a workload between lanes as needs change. Exposure and latency stay matched to each route.

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

Your most regulated records sit on the wrong side of the AI line because every model has to decrypt to compute.

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.