Employees, applications and agents reach models through one controlled layer. Every request is priced and attributed, checked on the way out so data does not leak, and on the way back so nothing hidden takes over.
People signed up for their own accounts because the work needed doing, and applications hard-wired one provider each. Nobody can now say what the organisation asks AI, what it costs, or what has left the network — and banning it only pushes that further out of sight.
One connection for commercial, open-weight and self-hosted models — point the Gateway at your own vLLM or Ollama, with a key only if your server asks for one. Applications stop depending on a single vendor.
Route by task, quality, sensitivity and cost, and reserve premium models for work that needs them. The console shows what the router chose and why.
How the Gateway picks a model →What counts as sensitive, and what counts as hard, is decided by a model we run — not by the vendor you are sending the request to. In Enterprise on-premise it runs on your hardware and nothing leaves it.
A provider outage, an exhausted quota or a rate limit, and another provider in the same class or above takes the request — only from models that application is allowed to use. The answer names the model that wrote it.
Every request tagged to a user, team, project or application, with hard and soft limits and alerts before the ceiling — so AI is a budget line, not a surprise invoice.
Inspect or block sensitive content before it leaves your network. What counts as sensitive is decided by a model we run — not by the vendor you are sending it to. What does not pass does not leave.
Whatever a tool brings back — an email, a web page, a CRM record — the model reads as data, not as a task. The same model spots an instruction nobody gave, in the same pass; in block mode the suspicious text never reaches the model. The same check covers events the Gateway hands on to your other applications.
How the Gateway spots an instruction nobody gave →Every request, model, decision and cost queryable later for a compliance or incident review. Each tool call shows how it was verified and what the check said about its result — and the whole record of a request saves as one document, HTML or PDF.
People keep the models they rely on, through an account the organisation can see. Adoption goes up and exposure goes down at the same time — nobody has to give up a tool.
Sensitive content is caught before it leaves, and what comes back is checked before a model reads it — so a hidden instruction meets a check, then tool permissions and approval gates, before it can turn a helpful answer into an action nobody approved.
Every request is attributed to a team, project or application, with limits set before the invoice arrives instead of explained after it.
Most exposure does not come from your applications — it comes from people doing their job through accounts nobody can see. Put your team behind the Gateway first, then the applications and agents.