Keep models, tools, and data
inside your environment
Run models privately on
Amazon Bedrock
Azure
Your own GPUs
The problem
Your data can’t go into a vendor’s AI product, but your people still need AI. Most AI platforms ask you to trust their cloud and their data agreement.
What changes when AI runs inside your environment
In the vendor’s cloud, under their data agreement
In your Kubernetes, in your cloud account, data center, or air-gapped
Public endpoints only
Models in your cloud account over a private connection, or open-weight models on your own GPUs
Another login to manage
Your identity provider, such as Okta, Entra ID, or a self-hosted Keycloak
Keys stored in someone else’s platform
Read from your vault at the moment of use
In the vendor’s console
In your environment, exported to your SIEM
Required
Not needed when you run air-gapped
How xpander helps
Everything runs in your Kubernetes.
01
Everything runs in your environment
Gateways, agents, the AI Workspace, memory, and logs, deployed into your Kubernetes.
02
Models where you want them
Models in your own cloud account over a private connection, or open-weight models on your own GPUs.
03
Your identity, vault, and SIEM
xpander plugs into what you already run, so nothing needs a new data path out.
04
Air-gapped when required
No internet connection needed.
