Why the LLM Gateway Is the Most Critical Brick in Your AI Platform

As enterprises move from AI experimentation to production-grade deployment, a pattern emerges: cost overruns nobody saw coming, security blind spots at the model layer, compliance gaps that regulators will not overlook, and a creeping dependency on providers whose pricing and roadmap you do not control.

These are not growing pains. They are architectural failures — and they all share the same root cause: the absence of a centralized control plane between your applications and the large language models they consume.

That control plane has a name. It is the LLM Gateway.

What we cover in the full article

In our latest publication, we lay out why the LLM Gateway deserves the same architectural gravity as your API Gateway or your identity provider — and why, in our view, it should be open-source and sovereign by default.

Seven capabilities. One infrastructure layer.

From real-time FinOps and token-level cost attribution, to prompt-level DLP and security enforcement, to model portability that eliminates vendor lock-in overnight — we break down each pillar with the level of technical depth that CIOs, CTOs, and CISOs need to make infrastructure decisions, not just strategy slides.

We also address a question too few organizations are asking today: if the LLM Gateway sees every prompt and every response your company generates, should that layer really be a black box operated by someone else?

Why this matters to us

At Polynom, the LLM Gateway is not a thought experiment. It is a core component of the AI platform infrastructure we design, deploy, and operate for European enterprises — from financial services and defense-adjacent industries to manufacturing and luxury.

Every agentic solution we build runs through governed, auditable, sovereign infrastructure. The gateway is where that governance starts.

Read the full article →

8-minute read. No fluff. Written for the leaders who sign off on AI platform architecture.