Bring AI to the data you can't move
Your most regulated records sit on the wrong side of the AI line because every model has to decrypt to compute.
For inference providers
Offer encrypted inference your customers actually trust.
Your customers ask if you ever see their prompts. "We delete logs" stopped being a good answer two years ago. The next generation of AI infra has to be unable to see what it serves.
VectaX as the FHE runtime under your inference. The promise you sell, you can mathematically keep.
Use cases for this audience
5 scenarios
Fine-tune on customer data without ever seeing it
Domain models need real customer data to be useful. Training in plaintext means you hold what you swore you wouldn't.
One endpoint for every model, with policy at the door
Each team hits its own provider its own way. Keys sprayed across services, prompts egressing in the clear, no single place that can say what was asked or whether it was allowed.
Pick the encryption posture per workload, not per gateway
Some routes need raw speed. Others need FHE all the way through. You shouldn't have to pick one for the whole org.
Stop your model from being cloned out the back door
Distillation attacks turn your API into someone else's competing model in weeks.
Get started
See encrypted AI security in action.
FHE-native inference. Runtime agent guardrails. Continuous red teaming. One platform. Book a working session with the team.