Glossary · Platform

What is an AI gateway?

An AI gateway is a service that sits between your applications and AI models, routing every request through a single control point where it can be secured, governed, logged, and cost-managed — the equivalent of an API gateway for LLM and agent traffic.

Last updated Jun 21, 2026

It's the equivalent of an API gateway, but for LLM and agent traffic — one place to apply policy instead of bolting controls onto every app.

What an AI gateway does

  • Routing & failover — one endpoint in front of many providers (OpenAI, Anthropic, Bedrock, Azure, self-hosted), with load-balancing and fallback.
  • Security — inspect requests and responses for threats like prompt injection, and apply DLP/PII redaction.
  • Cost governance — per-team and per-agent budgets, token attribution, and rate limiting.
  • Observability & audit — log every request for analytics and compliance.

Because it sits in the request path, a gateway can enforce policy in real time — not just observe it after the fact.

AI gateway vs. agentic trust plane

A basic AI gateway typically watches the prompt and response of a model. As applications became autonomous agents, that's no longer enough: agents also use retrieval, tools/MCP, session memory, and agent-to-agent calls. An agentic trust plane extends the gateway idea to inspect and govern all six surfaces, with adaptive security, real-time compliance, and cost control — see agentic AI security.

Self-hosted vs. SaaS AI gateways

  • SaaS gateways route your traffic through a third party — simple, but your prompts and data transit someone else's infrastructure, which complicates data residency and audits.
  • Self-hosted gateways run inside your own VPC with zero data egress — the gateway inspects every request while your data never leaves your network. This is the model regulated and security-led teams prefer.

TrustGate is a self-hosted AI gateway and agentic trust plane — see how it works.

FAQ

Is an AI gateway the same as an API gateway? Same idea, different traffic. An AI gateway is purpose-built for LLM and agent requests — adding model routing, prompt/response inspection, token-cost governance, and agent-surface security that a generic API gateway doesn't have.

Do I need an AI gateway if I only use one model? Often yes — even with one provider, a gateway centralizes security, PII redaction, cost limits, and audit, so you're not re-implementing those controls in every application.

See how TrustGate secures every agent surface.