Integration · AI Gateway

AI gateway: the governance rails between your AI agents and your core systems.

An AI gateway sits between AI applications and the models, tools, and agents they call, and applies identity, policy, and logging to every request. Duczer East implements AI gateways and agent controls for banks, insurers, and health systems, on the API and identity platforms they already run.

Implementations start at $50K. Only your email is required to size yours.

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DTCC
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DTCC
Koch
ExxonMobil
HCA Healthcare
Ryder
AAA Club Alliance
What it does

What an AI gateway does

Your API gateway already authenticates every application, enforces rate limits and access policy, and logs each call. AI traffic needs the same treatment and usually does not get it. Model calls go straight from application code to a provider. Agents reach tools through MCP servers with shared keys. Nothing records which agent acted, for whom, or under what policy.

An AI gateway closes that gap. It routes model calls, MCP tool calls, and agent-to-agent traffic through one governed point that applies authentication, policy, guardrails, and quotas, and writes the record your risk team will ask for. For a primer, read what an AI gateway is and when you need one. Not sure you need one yet? Ask for a free fit check.

Compared

AI gateway vs LLM gateway vs MCP gateway

The names overlap in vendor marketing. What matters is which traffic passes through a governed point and which goes around it.

LLM gateway, MCP gateway, and AI gateway compared by traffic, controls, and fit
Attribute LLM gateway MCP gateway AI gateway
Traffic it sees Calls to language models Agent calls to tools through MCP servers Model, MCP, and agent-to-agent traffic
Typical controls Provider routing, quotas, cost, and prompt and response guardrails Authentication, tool allow-lists, and per-tool policy All of these under one policy model
When it is enough Apps call models, but agents do not act on systems Agents act on systems through a small set of tools Agents call models and tools, and you need one evidence trail
Agent identity

Agent identity and delegation

Every agent needs its own identity: registered, scoped to least privilege, and revocable. When an agent acts for a person, the call carries both the agent and the person, so the record shows who authorized the action.

Shared service accounts and API keys in environment variables fail this test. We implement agent identity on your existing identity platform and connect it to the gateway, so policy can use the agent, the user, and the purpose of the call.

MCP security

MCP security

MCP is a protocol for giving agents context and tools. It is not an authorization model, and treating it as one is the most common gap we see. MCP security in a regulated firm means:

  • Every MCP server sits behind the gateway, never on a direct path to production data
  • Agents authenticate with their own identity before any tool call
  • Each agent has an allow-list of tools, with per-tool policy and rate limits
  • Every tool call is logged with the agent, the user, the tool, and the policy decision

Background: MCP is a context protocol. Most enterprises are letting it become an authorization model.

Decision logs

A record of every call

A decision log records what the agent was asked, what it called, what the gateway allowed or blocked, and what came back.

Stop control

Stop an agent in seconds

A stop control revokes an agent's identity or blocks its traffic at the gateway in seconds, without a code change. Both controls are tested before go-live, not described in a runbook after the first incident.

The gateway governs each call. Governing the agents themselves, from inventory and identity through evaluation and suspension, is the job of a control plane above it. For WSO2 customers that is WSO2 Agent Manager, which uses the AI Gateway as its enforcement point.

The evidence map

Every question a reviewer asks, and the system that answers it

This table is what most pilots cannot fill in. Each examiner question needs a record, and each record needs a system that produces it as the agent runs.

Questions a reviewer asks about an AI agent, the record that answers each, and the system that produces it
Question a reviewer asks Record that answers it System that produces it
Which agent took the action? Agent identity on every call Identity platform
On whose authority? Delegation record linking agent and user Identity platform and gateway
What did it touch? Access log per model, tool, and API call AI gateway
Under which policy? Policy decision logged with each call AI gateway
Was sensitive data exposed? Guardrail results on prompts and responses AI gateway guardrails
Can you stop it? Revocation and block events, with test results Identity platform and gateway

The governance program behind it is covered in AI governance consulting. For banks, the SR 26-2 evidence pack is covered in AI governance consulting for financial services.

Build or buy

Build or buy an AI gateway

Building your own gateway looks cheap for the first model provider and the first agent. The cost arrives later: every new provider, protocol change, guardrail, and audit request lands on your team.

For a regulated firm we usually recommend running a platform gateway for the governed core and writing custom policy only where the platform cannot express it. If your API platform already includes AI gateway capability, start there.

Platforms

Platforms we implement on

We implement AI gateway and agent controls on WSO2, MuleSoft, and Apigee.

WSO2 is where our practice goes deepest: the WSO2 AI Gateway and Agent ID can run, with their control plane, entirely inside your own infrastructure. See AI and agent governance on WSO2.

How an engagement runs

From a traffic review to a gateway that runs

Most engagements start with the AI traffic review. You can start at any stage, in English, Spanish, or Portuguese.

01

Review

A fixed-scope AI traffic review. We find every path from agents and apps to models, tools, and data, and mark which ones bypass governance.

02

Design

The gateway placement, identity model, tool allow-lists, guardrails, and logging.

03

Implement

Route traffic through the gateway in phases, with the old path kept until each cutover is proven.

04

Run

Monitoring from our network operations center, policy changes, and support. Delivered as support, managed services, or an outsourced integration team.

The same team runs AI gateways alongside API gateways, identity, and integration platforms; see managed integration services.

Size it or check it

Size your AI gateway, or find out if you need one

Ready to price it? Size it and see your likely tier as you answer. Still deciding? Ask for a free fit check and get a written answer.

  • Sizing: a quote within one business day. Pilot from $50K, Production from $75K, Enterprise platform from $125K.
  • Fit check: free, in writing, within five business days. You need one now, not yet, or what would change the answer.
  • Either way: only your email is required, and the reply comes from an engineer.

Only your email is required. Your likely tier updates as you answer.

Traffic to govern (optional)

Choose how many apps or agents will call models to see your likely tier.

  • Pilotfrom $50KOne app or agent and one model provider. Gateway with identity, token budgets, and call logging.
  • Productionfrom $75KUp to 20 apps or agents across providers. Guardrails, agent identity, decision logs, and a tested stop control.
  • Enterprise platformfrom $125KOver 20 apps or agents across teams. Model, MCP, and agent-to-agent traffic under one policy model, with evidence reporting.

Starting prices. Your quote is sized to your estate.

We reply with a sized quote within one business day. We save what you enter so we can follow up if you don't finish. See our privacy policy.

Questions

AI gateways, answered plainly.

AI gateways

Do we need an AI gateway if we already have an API gateway?

Often you can extend it. Many API platforms now include AI gateway capability. The test is whether model calls, MCP tool calls, and agent traffic actually pass through it with agent identity and policy applied. If they go around it, you do not have an AI gateway yet.

Is it worth building our own AI gateway?

Rarely for a regulated firm. A custom gateway leaves your team owning every provider integration, guardrail, and audit change. Use a platform gateway for the governed core and write custom policy only where the platform falls short.

Can an AI gateway run inside our own perimeter?

Yes. AI gateways and their control planes can run on-premises or in a private cloud, including air-gapped environments, so prompts, data, and logs stay where residency rules require.

How is an MCP gateway different from an API gateway?

An API gateway governs calls to APIs. An MCP gateway governs agents calling tools through MCP servers, which needs agent identity, tool-level allow-lists, and logging of each tool call. An AI gateway can do both under one policy model.

Is an AI gateway the same as an agent control plane like WSO2 Agent Manager?

No. The gateway is the enforcement point on the traffic path: it governs each call an agent makes to a model, tool, or API. A control plane such as WSO2 Agent Manager sits above it and governs the agents themselves: inventory, identity, lifecycle, evaluation, and suspension. The control plane uses the gateway to enforce its policies, and the gateway can run on its own.

What audit evidence should an AI gateway produce?

For every call: the agent identity, the user it acted for, the model or tool called, the policy decision, guardrail results, and the response status. Plus revocation and block events for the stop control.

Working with us

Who implements AI gateways for banks?

Look for a partner that has implemented gateways and identity in regulated environments, works across more than one platform, and designs the evidence your risk team needs, not only the routing. Duczer East does this on WSO2, MuleSoft, and Apigee.

Which platforms does Duczer East implement AI gateways on?

WSO2, MuleSoft, and Apigee. WSO2 is our deepest practice, including the WSO2 AI Gateway and Agent ID.

How much does an AI gateway implementation cost?

Our AI gateway implementations start at $50K for a pilot, $75K for production, and $125K for an enterprise platform. Agent tool access, or an on-premises or hybrid deployment, usually moves a project up one tier. The sizing form on this page shows your likely tier as you answer, and we reply with a quote within one business day.

Can you tell us whether we need an AI gateway yet?

Yes. Ask for the free fit check on this page. We reply in writing within five business days: you need one now, not yet, or what would change the answer. No call is needed.

Start here

Price it, or find out if you need it.

Size your AI gateway and get a quote within one business day, or ask for a free fit check and get a written answer within five. The first conversation is with an engineer, not a salesperson.