The quickest way to lose control of sensitive data is to let every team call an AI provider directly. Prompts end up containing access keys, customer records and incident details, and nobody can say which provider saw what.
A gateway in front of every model call fixes most of this, as long as it does four things.
1. Mask secrets before anything leaves
Prompts built from logs, tickets or configuration often contain credentials. The gateway should recognize common key formats, tokens, private keys and password fields, and replace them before the request reaches any model. In CloudVision360 this is on by default, and the number of redactions is recorded with each request.
2. Classify the request, then route it
Every request carries a data classification: public, internal, confidential or restricted. Tenant policy sets the highest classification that may go to an external provider. Requests above that ceiling go only to private models running in your own network, and if none is configured the request is refused rather than sent anyway.
Organizations that want no external AI at all can say so, and every request then stays on self-hosted models. That is how we run our own hosted service: customer data never goes to an external AI provider.
3. Limit what the model can do
A model should only see the tools its feature needs. The gateway filters each request to the feature’s allow-list, removes anything the tenant has denied, and records what it removed. Models never execute actions directly; they can only recommend actions that the policy engine already allows.
4. Record everything except the content
Each request is written to the audit trail with the feature, provider, model, prompt version, a SHA-256 hash of what was sent, token counts and cost. Storing full prompts and answers is off by default, so the audit trail doesn’t become a second copy of sensitive data. You can still prove exactly which prompt version produced an answer.
Quotas belong in the same place
Monthly budgets, per-user daily limits and per-feature quotas stop runaway costs and also limit how much data any one user or feature can push through a model.
Start with an inventory
If you don’t know which AI tools are in use today, start there. Our free AI Governance Assessment takes about five minutes and highlights the gaps that matter most.