Services · Govern

Every AI connection in your company, through one controlled gateway.

When every team connects AI tools directly to company systems, you get shadow integrations nobody governs. An MCP gateway provides controlled access to models, tools, and data — authentication, routing, logging, and usage controls in one place. Adopt AI fast without losing control of what touches what.

2–4 wk
Gateway deployed
Every request
Logged and auditable
One
Control point for AI access
The problem

Shadow integrations multiply faster than you can review them.

Marketing wires an AI tool into the CRM. Sales connects another to email. An engineer points an agent at the production database. Each connection made sense to someone — and none of them went through you. There's no inventory of what AI can touch, no log of what it did, and no way to shut one connection off without breaking five workflows.

The answer isn't banning AI tools. It's giving every person and every agent one governed route to the systems they need. That's what an MCP gateway does: one place where access is granted, requests are logged, and limits are enforced.

What you get

A gateway your security team can stand behind.

We design and deploy the gateway, wire it into your identity stack, and hand your team the controls. Running infrastructure, not an architecture diagram.

01

MCP gateway, designed and deployed

The core build. One gateway between your people, your agents, and your systems — every request authenticated, routed, logged, and subject to limits you set. Scoped to your environment, deployed on your infrastructure, operated by your team.

Scope your deployment →
  • MCP gateway design and deployment
  • Authentication and access controls per user and per agent
  • Routing across models and tools
  • Full request logging for audit and review
  • Usage controls and quotas
  • Integration with your identity stack
02

Governance that doesn't slow teams down

Guardrails that block the bad paths without adding a ticket queue to the good ones. Teams keep the tools they like — access just runs through a route you can see, log, and revoke. Adoption speeds up when nobody has to ask permission twice.

Talk through your policy needs →
03

Visibility from day one

Full request logging means questions like "what did that agent access last Tuesday" have answers. Usage data shows which tools earn their keep and which connections nobody uses — the inventory you never had, generated as a side effect.

Ask about logging and audit →
Who it's for

If this sounds familiar, this is for you.

A gateway matters most at the moment AI adoption outruns AI oversight.

IT and platform leaders
You're expected to enable AI across the company and keep it controlled — usually with the same headcount you had last year.
Security teams governing AI adoption
You need to know what AI touches, prove it to auditors, and revoke access in one move — not by hunting down each team's API keys.
Enterprises scaling from 5 to 500 AI users
The pilot phase ran on trust. The rollout phase needs authentication, quotas, and logs before the user count adds a zero.
Companies in regulated industries
Legal and compliance need a defensible answer to "what can AI access" — a gateway makes that answer a report instead of an investigation.
Related services

Where this fits in the stack.

The gateway is the control layer. These services cover what runs through it and around it.

AI Security Assessment
Know your AI security, privacy, and compliance exposure — and exactly what to do about it.
Explore →
Agentic workflow automation
Agents that execute recurring business processes — in production, not in demos.
Explore →
Citizen SDLC
Your employees are already building AI tools. Give them a road to production.
Explore →

Adopt AI fast. Keep control of what touches what.

A scoping call takes 30 minutes. You leave knowing what a gateway looks like on your stack and how long it takes to stand up.