Why Use an AI Gateway Instead of Calling OpenAI, Anthropic, or Azure Directly

Last updated: September 2026

The reason to use an AI gateway is control. The gateway gives you one endpoint, one set of credentials, and one place to enforce policy for every AI request in the organization. Calling providers directly works for one application and one provider. Once several teams use several providers, and finance asks who spent what, the gateway is the only layer that covers all of them.

Why use an AI gateway instead of direct provider calls: the problems start with the second team

A direct integration is one SDK, one key, and one base URL. The problems start when the same pattern repeats across the company:

Situation	What breaks with direct calls
Five teams each have their own OpenAI key	No one can report spend by team without collecting five invoices
One team wants Claude, another wants GPT, a third runs a self-hosted model	Every application carries provider-specific code and credentials
A provider has an outage	Every application fails at once, and each team writes retry logic on their own
Security asks whether customer data went to a model	No single log exists to answer the question
Finance sets a spend limit	No control point exists to enforce the limit

Tetrate’s post on the AI gateway as a meta-provider reports survey data that 78% of companies ran two or more model families. With two or more model families, the gateway becomes the control point, and each provider becomes one option the gateway can pick.

A gateway changes one line of code and adds six controls

Tetrate Agent Router Enterprise accepts the OpenAI Chat Completions API and the Anthropic Messages API. To move an application onto the gateway, you change the base URL and the API key. The application code stays the same. From then on, every request receives these controls:

Control	What the control does	Docs
One endpoint for every model	12 provider families and 200+ models behind one URL	Supported providers
Fallback	When a provider returns 429, 5xx, or times out, the gateway retries the next backend in the chain	Fallback policy
Cost attribution	Every request is logged by user, team, API key, model, provider, and tag	See where AI spend is going
Budgets and rate limits	Watch spend, Hard stop, or Degrade gracefully to a cheaper model at a spend cap	Budgets
Guardrails	Redact PII and secrets, or block prompt injection, inline at the gateway	Guardrails
Credential control	Operators hold provider keys; developers receive gateway keys tied to SSO identity	Developer On-Ramp

The gateway also adds traffic splitting between models, an audit log that cannot be changed, and OpenTelemetry export. An MCP gateway covers tool traffic. The product overview lists the full set.

Provider credentials never reach developer machines

With direct calls, each developer keeps a provider key. Keys get copied into shell history, CI logs, and shared documents. When a key leaks, the only fix is to rotate the provider key and update every application that uses the key.

With the gateway, operators configure provider credentials once in the Admin Console. Developers sign in with SSO and receive a gateway key scoped to a project. The key concepts page explains that a gateway key can be canceled or given a budget without any change to a provider account.

The gateway also combines existing provider contracts behind one model name

Large organizations hold several provider subscriptions at once: Anthropic through AWS Bedrock in one region, OpenAI through Azure in another, plus direct accounts. The gateway connects each subscription as a separate provider entry and maps one model alias to all of them. Applications ask for claude-sonnet-5 and the gateway decides which contract serves the request. Teams that already have their own provider contracts can bring their own keys. A private network connection through AWS PrivateLink, Azure Private Link, or GCP Private Service Connect keeps the traffic off the public internet.

Azure API Management covers Azure, and an AI gateway covers every cloud and every coding agent

Teams on Azure ask why Azure API Management is not enough. Azure API Management handles requests to models inside Azure. Azure AI Foundry accepts either API Management or an outside gateway as the bring-your-own-model connection for agents. The difference is coverage. API Management ties the control point to Azure. Tetrate Agent Router Enterprise runs in AWS, Azure, and Google Cloud under one control plane. The gateway also covers coding agents such as Claude Code and GitHub Copilot, and MCP tools, which never use Azure. Calling Azure OpenAI directly has the same limit as calling any provider directly. Every team gets a key, spend stays hidden until the bill arrives, and nobody sets a shared policy. Hidden spend and missing policy do not depend on where the model runs.

An AI gateway adds about two milliseconds of latency per request

The main concern about a gateway is latency. Agent Router is built on Envoy, the same proxy that carries traffic at Google, Lyft, and most large Kubernetes deployments. Tetrate’s LiteLLM comparison cites an independent benchmark of about 2 ms of gateway delay per request, and the delay does not grow under heavy traffic. Model inference takes hundreds of milliseconds to many seconds, so the gateway adds well under 1% to response time.

The second concern is a new component to operate. Agent Router Enterprise splits into a Tetrate-hosted management plane and a data plane. You can run the data plane in your own Kubernetes cluster or let Tetrate run the data plane. The deployment models page describes the choices. The data plane keeps routing if the management plane cannot be reached.

When not to use an AI gateway: one team, one application, one provider

A gateway is not worth adding in these cases:

One application, one provider, and one team own all AI usage, and no one else will join.
No compliance requirement exists to log or redact prompts.
Spend is small enough that the provider invoice is the only report anyone needs.
The application uses a provider feature the gateway cannot translate. For example, the Responses API routes only to OpenAI and Azure OpenAI, so cross-provider fallback is not available for those requests.

If any of those four conditions changes, you can add the gateway later.

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Frequently asked questions

What is an AI gateway? An AI gateway is a proxy that runs between applications and AI model providers. Applications send requests to the gateway, and the gateway authenticates the caller, applies policy, picks a provider, forwards the request, and records the result.

Does an AI gateway require code changes? Only the base URL and the API key change. The gateway accepts the OpenAI Chat Completions format and the Anthropic Messages format, so existing SDKs keep working.

How much latency does a gateway add? An Envoy-based gateway adds about 2 milliseconds per request. Model inference takes far longer, so the overhead is under 1% of total response time.

Can I keep my existing provider contracts? Yes. Each subscription becomes a provider entry in the gateway. One model alias can map to several entries, and the gateway picks between them.

What happens if the gateway itself goes down? The gateway’s data plane runs as multiple replicas in Kubernetes. Configuration is cached locally, so the data plane keeps routing even when the management plane is unreachable. DNS-level failover between gateway sets is also supported.

Is an AI gateway different from Azure API Management? Azure API Management fronts models inside Azure. An AI gateway such as Agent Router runs in AWS, Azure, and Google Cloud under one control plane. The gateway also covers coding agents and MCP tools. Azure AI Foundry can send agent traffic to either one.

When should I not use an AI gateway? Skip an AI gateway when one team owns one application on one provider. The team must also have no compliance need to log prompts, and spend too small to assign by team.

Which APIs does an AI gateway accept? Agent Router accepts the OpenAI Chat Completions API and the Anthropic Messages API for every provider. The OpenAI Responses API routes only to OpenAI and Azure OpenAI.

How many models can an AI gateway route to? Agent Router connects to 12 provider families and more than 200 models through one endpoint, including self-hosted OpenAI-compatible models.