Every AI connection in your company, through one gateway you control.
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 through authentication, routing, logging, and usage controls in one place. It runs on your infrastructure, and the control point stays in your hands rather than a vendor's.
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 is 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 is not banning AI tools. It is giving every person and every agent one governed route to the systems they need. That is what an MCP gateway does: one place where access is granted, requests are logged, and limits are enforced. Owning that layer matters, because whoever operates the gateway sees every question your company asks its own data.
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.
MCP gateway, designed and deployed
The core build. One gateway between your people, your agents, and your systems, with every request authenticated, routed, logged, and subject to limits you set. Scoped to your environment, deployed on your infrastructure, operated by your team, and owned by your company.
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
Governance that does not slow teams down
Guardrails that block the bad paths without adding a ticket queue to the good ones. Teams keep the tools they like, and access simply 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 →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, producing the inventory you never had as a side effect.
Ask about logging and audit →If this sounds familiar, this is for you.
A gateway matters most at the moment AI adoption outruns AI oversight.
Where this fits in the stack.
The gateway is the control layer. These services cover what runs through it and around it.
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.
