Running the Models in Your Own Cloud

Some client contracts enumerate exactly which third parties may handle their data. If yours do, adding an AI vendor to that list can mean going back to your client for consent before you can use AI at all. You can avoid that entirely: point StrikeOps at models running inside your own cloud account.

You create a role granting access to the models you want, scoped as tightly as you like. StrikeOps assumes that role using an identifier issued to you alone, and inference runs on your infrastructure in the region you select. The model vendor never receives the request, because the model runs as a deployed copy inside your account rather than as a call out to the vendor's own service. There is no AI provider to add to your subprocessor list.

StrikeOps orchestrates the request, so the platform stays in the path as your existing processor under the agreement you already hold with us. What changes is that no model vendor joins it.

What this gives you

• No AI vendor to add to your subprocessor disclosures, so client contracts that enumerate processors stay as they are.
• Inference stays in the cloud region you select, evidenced by your own logs rather than a vendor attestation.
• Every inference call lands in your own audit trail, alongside the rest of your infrastructure.
• Inference spend sits inside your existing cloud commitment, billed to your account.
• The role you create is revocable at any time, and revoking it stops inference immediately.

What stays the same

• StrikeOps orchestrates the drafting and remains a processor under your existing agreement with us.
• Your operators still review and approve every section before a client sees it.
• Data at rest is still encrypted under your own key, which is separate from model access.