An agent gateway is the control point an autonomous agent passes through when it calls a model, queries a database, or reaches an external tool. Operators use that point to enforce authentication, spend limits, logging, approval rules, and emergency stops. Teamcopilot describes the pattern as a control plane for enterprise AI: one layer that decides what an agent may do before the request reaches production systems.
The demand is practical. A platform team needs to know what an agent called, which credential it used, what it cost, and how to stop the run if behavior drifts.
Three products already use adjacent language, with different deployment shapes.
| Vendor | Shape | What it centers on |
|---|---|---|
| Arcade | In-VPC runtime, one-click deploy | Authorization and tool execution |
| AWS Bedrock AgentCore | Managed cloud runtime | Hosted agent execution |
| Nutanix Agent Gateway | On-prem appliance (Enterprise AI 2.7 GA) | Data-plane control inside a private environment |
Arcade moved first on distribution. On July 3 it listed its authorization and tool-execution runtime on the Azure and AWS marketplaces, giving teams a way to deploy an in-VPC gateway and keep credentials on their own network. Two days later Forbes surveyed the field and framed agent gateways as an emerging enterprise AI control plane.
The label is catching up to already-shipping products. A runtime, a managed service, and an on-prem box all sit near the same buyer problem: agents need a governed path into systems of record. An ops lead evaluating the category should start with one question: where do the credentials and audit log sit?
The category is young.
Watch the Azure and AWS marketplace listings through Q3. The next vendor to ship under "agent gateway" will show whether buyers treat the term as authorization, runtime, or a broader control surface spanning both.
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